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Thesis: Author: Department of Finance Thomas Pedersen Supervisor: Jan Bartholdy
Stakeholder Theory -lessons from Denmark
Aarhus School of Business 2004
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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I. Introduction ................................................................................................................... 1 1. Introduction................................................................................................................. 1
1.1 Problem statement................................................................................................. 2 1.2. Structure............................................................................................................... 2 1.3. Delimitations........................................................................................................ 4
II. Theoretical framework................................................................................................ 4
2. Shareholder capitalism................................................................................................ 4 3. Beyond shareholder capitalism................................................................................... 8
3.1. Ethics and morality .............................................................................................. 9 3.1.1. Approaches to ethics ................................................................................... 10 3.1.2. Ethics and the law ....................................................................................... 12 3.1.3. Relativism ................................................................................................... 13
3.2. Ethics and business ............................................................................................ 14 3.3. Corporate social responsibility .......................................................................... 15
4. Stakeholder theory .................................................................................................... 17
4.1. Emergence of the stakeholder society................................................................ 18 4.2. Voluntarism........................................................................................................ 21 4.3. Stakeholder theory and property rights.............................................................. 22 4.4. Justification of stakeholder theory ..................................................................... 22
4.4.1. Descriptive justification .............................................................................. 24 4.4.2. Instrumental justification ............................................................................ 25 4.4.3. Normative justification ............................................................................... 29
4.5. Stakeholder identification .................................................................................. 30 4.5.1. Identification typology................................................................................ 32 4.5.2. Stakeholder classes and salience................................................................. 34
III. Empirical analysis .................................................................................................... 38
5. Selection of stakeholder groups ................................................................................ 39
5.1. Customers .......................................................................................................... 40 5.2. Shareholders....................................................................................................... 41 5.3. Environment....................................................................................................... 42 5.4. Employees.......................................................................................................... 42 5.5. Excluded stakeholders ....................................................................................... 43
6. Stakeholder assessment criteria ................................................................................ 43
6.1. Customers .......................................................................................................... 45 6.2. Shareholders....................................................................................................... 45 6.3. Environment....................................................................................................... 46 6.4. Employees.......................................................................................................... 47
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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7. Purpose, methodology and data ................................................................................ 49 7.1. Hypotheses......................................................................................................... 49 7.2. Statistical method............................................................................................... 51 7.4. Data .................................................................................................................... 54
7.4.1. Sample......................................................................................................... 55 7.4.2. Data collection ............................................................................................ 56 7.4.3. Time frame.................................................................................................. 58 7.4.4. Independent variables ................................................................................. 58 7.4.5. Financial data and performance measures .................................................. 60 7.4.6. Missing data ................................................................................................ 61 7.4.7. Construction of datasets.............................................................................. 61
8. Results....................................................................................................................... 62
8.1. Descriptive statistics .......................................................................................... 63 8.2. Simple regression............................................................................................... 67 8.3. Multiple regressions........................................................................................... 72
8.3.1. Final combination of variables.................................................................... 75 8.4. Compare means.................................................................................................. 78
IV. Concluding remarks................................................................................................. 81
9. Shortcomings ............................................................................................................ 81 10. Suggestions for future research............................................................................... 83 11. Conclusion .............................................................................................................. 84 Bibliography ................................................................................................................. 87 List of appendices ......................................................................................................... 92 List of figures................................................................................................................ 93 List of tables.................................................................................................................. 93
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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I. Introduction
1. Introduction
In today’s rapidly changing business environment a number of corporate managers,
researchers and theorists still rely heavily on the notion that the sole responsibility of a
corporation is to maximise the value of its owners. This US based approach, which can be
defined as shareholder capitalism, is also implicitly the basis for most financial theory
used today, and is based on classical economic and financial theory. Due to the
implicitness of shareholder capitalism in financial theory, corporate responsibilities that
extend beyond maximising shareholder wealth are rarely discussed in finance literature.
In most modern management theory, classic ethical theory is applied, in contrast to
shareholder capitalism. This puts emphasis on the modern corporation’s responsibilities
towards other stakeholders than merely the owners. The stakeholders are those who can
affect or are affected by the achievement or the company’s objectives (Freeman, 1984).
These responsibilities that corporations have towards the stakeholders exceed those
required by law, and attending to them may not always be the best way of conducting
business from a financial standpoint. This fundamentally different view of corporate
responsibilities has mainly gained popularity in Europe.
Many of the theories and opinions incorporating morality in corporate responsibilities
accept that this is done at the cost of shareholder wealth. Stakeholder theory, on the other
hand, holds that maximising the value of one’s stakeholders will also maximise the value
of the whole company. This was the original thought of Freeman (1984), but there is still
some doubt whether this is, in fact, true. So far the evidence linking stakeholder theory
with improved financial performance is limited, and only few have attempted a thorough
analysis of the relationship1.
1 And to the writer’s knowledge no one has attempted such a study in Denmark.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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1.1 Problem statement
As a consequence of the lack of valid studies regarding stakeholder theory in Denmark as
well as internationally the purpose of this thesis is to test the theory empirically. The
central dilemma is what Donaldson & Preston (1995) refer to as the instrumental thesis,
namely the belief that:
Adopting a stakeholder oriented management style will result in improved
financial performance.
It is essential to understand how stakeholder theory has evolved, including knowledge of
the ethical theory which stakeholder theory is based upon and contrasting theory in form
of shareholder capitalism. A theoretical understanding is however not sufficient, to
properly deal with the issue. Due to the lack of previous studies, an empirical analysis is
required. This incorporates selecting relevant stakeholder groups and linking the
satisfaction of those to financial performance. A model will be built to attempt to
formalise this link. In the process of testing stakeholder theory other aspects, such as the
developments of stakeholder focus in Denmark are also examined.
1.2. Structure
The thesis is divided into four main parts, the first of which is the introduction. Part I thus
includes a formal introduction and problem statement, as well as this overview of the
structure, and finally a section on the delimitations of the thesis.
In order to provide the reader with sufficient theoretical knowledge to clearly understand
the empirical analysis, Part II of the thesis presents the underlying theoretical framework.
The theoretical part begins with the traditional view of shareholder capitalism and then
moves on to ethical theory and corporate social responsibility. This naturally leads to the
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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introduction of stakeholder theory, which includes discussions of validity of the theory
and how to determine which stakeholders are relevant.
Part III deals with the empirical analysis. Initially it is necessary to determine which
stakeholders are relevant to a Danish based study, thus applying the theory from Part II.
After selecting who the stakeholders are, and how these are deemed satisfied, various
statistical analyses are carried out. First, the development of stakeholder focus in
Denmark will be mapped as a natural part of the data collection process. Next, the
analyses will test the relationship between the satisfaction of various stakeholder groups
(individually as well as combined) and financial performance.
Finally Part IV presents a discussion of the shortcomings of the analysis and suggestions
for future research, after which some concluding remarks are presented. Figure 1
visualises the structure of the thesis.
Figure 1: Structure of the thesis
1. Introduction
4. Stakeholder theory
3. Beyond shareholder capitalism
2. Shareholder capitalism
5. Selection of stakeholders
10. Suggestions for future research
9. Shortcomings
8. Results
6. Assessment criteria
7. Purpose, method & data
10. Conclusion
I.
IV.
III.
II.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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1.3. Delimitations
As the main focus of this thesis is stakeholder theory, discussions of conflicting and
complementing theories are only included to the extent necessary for the understanding
of stakeholder theory. This means that theories such as agency theory, corporate social
responsibility, ethics and morality are not investigated or tested in detail. More specific
management tools such as Balanced Score Card and intellectual capital statements are not
included at all.
Regarding the empirical analysis a number of stakeholder groups will be selected for
further analysis. Although many others are also interesting it is beyond the scope of this
thesis to thoroughly discuss and analyse them all. The statistical tests will be limited to
simple and multiple regressions and independent sample t-tests. The sample investigated
is limited to 89 of the companies on the Copenhagen stock exchange and the results are
therefore only directly applicable to those. Limitations of the sample used and the
statistical methods and tests are included in section III.
II. Theoretical framework
2. Shareholder capitalism
One of the assumptions behind much financial theory is that the only goal of a company
is to maximise its value, and thus maximise the wealth of the shareholders. This
assumption implicitly states that shareholders are only interested in increasing their
personal wealth. Any action taken by management that does not result in increased
wealth is, therefore, not in their interest. If management does not act according to the
owners’ preferences an agency problem occurs. Agency theory focuses on the
relationship between a principal (shareholders) and the agent (management) who is
supposedly looking after the interests of the shareholders2. The principal-agent problem
2 A detailed discussion of the agency-theory can be found in e.g. Jensen & Meckling, 1976.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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then arises when management fails its task of acting in the best interest of the
shareholders. If the shareholders have instructed management to maximise their wealth,
and management then makes decisions that do not result in a maximisation of the value
per share, a classical agency problem will occur. The result of such a problem will
typically be the termination of the current management3.
Shareholder capitalism and agency theory form the basis of most finance textbooks and
U.S. developed theories, which is also why this approach is often labelled the Anglo-
Saxon approach. The introductory finance text book from Ross, Westerfield & Jordan
(1998) cites the goal of financial management as maximising the current value per share.
They discuss how the shareholders are supposed to make management act in their best
interest, and only briefly mention the existence of other stakeholders4. Other text books
such as Grinblatt & Titman (1998) barely touch on the subject of what a company should
strive to achieve. These books implicitly assume maximisation of shareholder wealth as
the overruling goal of a company. To find reasons and opinions on why this is so, it is
necessary to turn to classical economic as well as management literature.
Perhaps the most frequently quoted and one of the greatest proponents of shareholder
wealth maximisation is Milton Friedman. Friedman (e.g. 1962, 1970, 1981), who is
probably best known for his macroeconomic writings, has continuously stated that the
only responsibility of a company is to make profits for its owners. Fundamentally,
Friedman sees himself as a believer in freedom. Government should play a minimal role
and mainly function as an umpire. The role of umpire for government is not unimportant,
but should be minimised. Although a certain degree of government power is unavoidable
the market should be controlled by the free market forces. This also means that he is a
proponent of no (or low) taxes, no forced pension funds etc.
3 For this problem not to occur too often, aligning management’s interest with those of the shareholders, through e.g. incentive plans, can be very effective in minimising the costs associated with the agency problem. Such incentive plans are outside the scope of this thesis. 4 See section 6 for further elaboration on the term stakeholder.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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Friedman is often referred to as a libertarian. This reference evolved from the term liberal
and refers directly to the importance these economists attach to the freedom of the
individual. For individual freedom to persist Friedman (1962) holds economic freedom in
very high regard. From his point of view economic freedom is one of the cornerstones of
individual freedom in the sense that if a person does not enjoy total economic freedom
this will be an obstacle for freedom as such. Friedman also refers to Adam Smith and his
book “The Wealth of Nations” (1776) when emphasising that an individual will promote
the well-being of society more effectively when pursuing his own interest, rather than
when he really strives for positive social results. Smith (1776) claims that he has, in fact,
never experienced a positive result from those who strive to achieve public good.
Roughly two centuries later Friedman comes to a very similar conclusion. At that point in
time business leaders have started paying attention to the social responsibility of the
company. Friedman’s opinion of the responsibility of a company is best summed up in
his own words:
“…there is one and only one social responsibility of business – to use its resources and
engage in activities designed to increase its profits so long as it stays within the rules of
the game, which is to say, engages in open and free competition, without deception and
fraud.”
Friedman, 1962. P.133.
From this it is evident that Friedman, but also Smith, sees the company as nothing more
than an instrument of the stockholders who own it. It is to serve as a vehicle for the
owners to generate more wealth solely for themselves (within the limits of the law). This
should be done without taking other stakeholders into account or exercising socially
responsible behaviour. Friedman sees the call for socially responsible management as
sheer socialist propaganda and an undermining of the free economy as such. That is also
the reason why he, somewhat atypically, holds that increasing profits is actually social
responsibility. This so-called shareholder capitalism stance holds property rights in very
high regard, which implies that the owners of the company have the right to the wealth
generated by the company they own (Werhane & Freeman, 1997). Friedman, Smith and
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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their followers can therefore also be classified as ethical egoists. According to the
believers of ethical egoism people should always act on the basis of perceived self-
interest (Beauchamp & Bowie, 2001)5.
Besides traditional economic and financial theory, social theory also backs up Friedman’s
statements to some extent by pointing towards a separation of law and morality. Legal
positivism and legal realism points towards nothing being above the law, and that it is of
no importance if the law is in conflict with moral norms. Also, the noncognitivist
perception of morality considers morality as being strictly a subjective and personal
matter (see section 3.1.3 on relativism). This means that morality cannot be generalised
and thus used in social theory (Andersen & Kaspersen, 2000). These different theories all
support Friedman and his compatriots; and they point to the shareholders right to expect
management to maximise their wealth, within only the limits of the law.
Friedman and Smith are frequently cited by defenders of strict shareholder capitalism.
This puts focus on freedom as an individual, not a collective, right. Nonetheless, the
consequence of their arguments, namely the sole focus on shareholder value, has also
been supported by more moderately minded writers. It is thus possible to support
shareholder capitalism in a more moderate manner. Jensen (2001) emphasises that
management should only focus on maximising the total value of the company. By total
value he refers not only to the value of the equity, but also the value of all other financial
claims such as debt and preferred stock. Jensen argues that for management to be
effective, the objective function of the company must contain only one objective. More
objectives will require trade-offs between the competing interests, and Jensen holds that
management will not be able to make these trade-offs efficiently, thus preventing them
from making purposeful decisions. Jensen thereby dismisses the stakeholder approach of
focusing on the interest of various groups by stating that it will result in poor decision
making. He does, however, choose to include e.g. debt in his objective function by
emphasising the focus on total value. Creditors, and therefore also debt are, in fact,
5 Ethical egoism is a normative theory which is discussed in sections 3.1.1. and 4.4.3. for elaboration of normative theories.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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sometimes characterised as stakeholders and are most definitely not comparable to the
shareholder wealth maximisation approach in its strictest sense6. Therefore, Jensen allows
this broader term to define the objective of the corporate objective function, and after all,
to some extent, adopts a stakeholder approach - or at least a broader definition of
shareholder capitalism than the one supported by Smith and Friedman. He partly
acknowledges this by reminding the reader that a company cannot maximise its value if it
ignores its stakeholders. Jensen therefore suggests what he calls enlightened stakeholder
theory. This enlightened value maximisation focuses on the long term maximisation of
the company’s total value by taking other stakeholder interests into account, while only
striving to maximise shareholder value.
Jensen in principle acknowledges stakeholder theory, but remains focused on shareholder
wealth through total value, which is why he is categorised as shareholder focused. He
does not give any indication as to how he sees his suggested approach being
implemented, nevertheless the notion that it is possible to maximise the total value of a
company through satisfaction of various stakeholder groups is important for this thesis. In
a sense Jensen goes a long way in attempting to bridge the gap between the two
conflicting theories by pointing out that the agency problem that arises from adopting a
stakeholder approach might actually not be all that important. Maybe an adoption of
stakeholder theory will even lead to maximisation of shareholder wealth.
It is important to bear in mind that many theorists and practitioners do not acknowledge
profit maximisation as the sole purpose of a corporation. Furthermore, they do not regard
the shareholders as the only, or even most important, stakeholder group.
3. Beyond shareholder capitalism
The continental European approach to wealth maximisation is somewhat different from
the Anglo-Saxon one described in the previous section. The sole focus on shareholder
wealth is exchanged for a view that incorporates morality and social responsibility, thus 6 A discussion of capital structure is beyond the scope of the thesis.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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treating the corporation as a person with duties and responsibilities. The individualism of
the Anglo-Saxon way is thereby questioned as focus shifts to the more collegial approach
that incorporates the long term interests of all concerned parties.
Traditional theories of ethics and morality, as well as a different perception of corporate
responsibilities are therefore integrated in management attitudes. This is ultimately what
triggers the emergence of stakeholder theory as well.
3.1. Ethics and morality
At the centre of the European approach is a different perception of ethics and morality
than that of Smith, Friedman and other defenders of shareholder capitalism. In the
continental approach the notions ethics and morality are central, and therefore it is
important to clarify, and distinguish between, those terms. Beauchamp & Bowie (2001)
defines morality as being concerned with social practices defining right and wrong.
Morality thus refers to the principles and rules of moral conduct in a society; principles
that exist are passed on from generation to generation and exist indifferently of the
individual’s acceptance of them. In this sense the definition of morality is very broad, and
certainly exceeds the belief and attitude of any individual. Freeman & Gilbert (1988)
define this common morality as the rules that most people conform to most of the time,
and as the rules that cover most of the situations that an individual might face at some
point in time. For instance common moral standards prevent most people from resorting
to violence, encourage respect for other persons and property and inspire a desire to help
others if the cost to one self is not very great. Freeman & Werhane, 1997 add obeying the
law, keeping promises and honouring contracts and avoiding lying and cheating to the list
of common moral standards.
Ethical theory, on the other hand, focuses on the personal reflection of morality in
society. This implies that the individual is not satisfied by simply conforming to these
moral standards; most people have a desire to understand morality and develop ones own
interpretation. Such an understanding will equip the individual with options when it
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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comes to dealing with moral problems to which the moral standards of society have no
solution. An insight into the moral standards of a certain society might help provide
answers to such questions as: are these the right standards for me? Why is something
defined as wrong or right? Why are certain actions required? Ethics is therefore a way of
understanding, adapting and justifying the standards to which you conform. According to
Beauchamp & Bowie (2001) there is a tendency to use ethics as a general term referring
to both moral beliefs and ethical theories.
Throughout this thesis both terms will be used. Morality refers to the standards of a
certain society or culture whether accepted by the individual (or company) or not. Ethics,
however, are moral standards that are accepted, and may also contain beliefs that exceed
the pre-set standards of the individual society/culture. Ethics thus incorporates morality.
3.1.1. Approaches to ethics
Studies of ethics in society and business take the form of one of three different
approaches, descriptive, conceptual or normative (Beauchamp & Bowie, 2001 and
Freeman & Werhane, 1997). Descriptive studies empirically describe the norms and
attitudes of various groups. Attitudes and norms often described include business relevant
issues such as sexual harassment and corporate ethical standards. In this sense the
descriptive studies are simply ethical observations that are supported by factual evidence.
Conceptual or analytical ethics, as they are also called, compare and analyse differences
rather than simply map norms and attitudes. These can be differences between different
religions, cultures or perhaps corporate philosophies and cultures (e.g. the comparison of
shareholder capitalism and stakeholder theory). Neither the descriptive nor the conceptual
approach to ethics have a prescriptive nature, they simply deal with the norms, tendencies
and attitudes and back them up with factual evidence. The third approach, the normative
approach, is however prescriptive. Normative ethics judge what is wrong and what is
right. In this sense the whole discussion of whether shareholder capitalism is right or
wrong is a normative approach to ethics (see section 4.4.3. for further elaboration). As
mentioned in section 2, Friedman (1962) states that the only responsibility of a
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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corporation is to maximise profits, and as this is merely his idea of what is right it can be
perceived as a normative theory. Another example is the theory of ethical egoism, which
holds that one should only take the welfare of others into account insofar as it has an
effect on one’s own welfare (Lyons, David in Freeman & Werhane, 1997, p. 641).
A number of normative theories oppose the views of the ethical egoists, Friedman and the
likes. One such normative theory is utilitarianism. This theory holds that actions and
practices must maximise the benefits of all those involved and minimise the harm
caused7. By focusing on all those involved the individual is of little importance; gender,
nationality, social position, race etc. will not lead to differential treatment. Having said
that, it is important to note that “all involved” also means that differential treatment may
occur in order to maximise the total benefits and minimise total harm. Therefore the law
should be designed to accommodate the masses, not individuals or minor groups (for
more on ethics and the law, see 3.1.2.).
Another classical school of thought that has been popular in modern history is
Kantianism8. Based on Immanuel Kant’s work on ethical theory, Kantianism holds
respect for persons in very high regard. Following the respect-for-persons principle an
individual should never treat another individual purely as a means to their personal ends
(Beauchamp & Bowie, 2001). This does not mean that one cannot benefit from the
actions of others, it merely implies that exploiting others solely for one’s personal benefit
is not acceptable. Hence, as long as the relationship is voluntary and beneficial to all
parties implicated it is acceptable. A good example of this is the relationship between
employee and employer in modern corporations. A problem can be the definition of ends
and means, when does e.g. the employee benefit enough from the employers decision to
hire him/her? When is this an end for the employee and not merely a means to an end for
the employer? These questions are hard to answer, and one would most likely get a
7 For a more detailed discussion of utilitarianism, see e.g. Freeman & Werhane (1997) or Beauchamp & Bowie (2001). 8 For a more detailed discussion of Kantianism, see e.g. Freeman & Werhane (1997), Beauchamp & Bowie (2001) or Andersen & Kaspersen (2000)
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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different answer depending on position, culture, political belief, religious belief etc. of the
person you ask.
As it obviously is not possible to rely on the differing perceptions of ethics to guide the
entire population of a modern civilisation, certain legislative initiatives are required to
provide a frame for people to act within. Nevertheless, it is important to note that the law
cannot possibly specify what is ethical in every situation. As established by utilitarianism
the law may not always provide the most fair guide line for the individual as it must be
designed to accommodate the masses.
3.1.2. Ethics and the law
Friedman (1962) holds that as long as the corporation acts within the limits of the game
and the law it is not engaging in any improper business. But according to Beauchamp &
Bowie (2001) it is important to note that because something is legal it is not necessarily
ethical. Also, if something is illegal it is not necessarily unethical. The law attempts to
translate morality into clear guidelines, but “grey” areas will always persist as it is
virtually impossible to cover all possible issues. Nevertheless, if something is illegal it is
often also unethical, whereas an obvious translation of ethical could be actions that
extend beyond what is required by law in regards to morality. This points to the fact that
the law is, in some cases, not enough to make individuals and corporations behave
ethically. In this connection it is very important to note that acts based on an individual’s
conscience are not by definition ethical. Conscience is individual and such acts may fall
outside of what society deems morally correct and thus ethical, or they may just as likely
extend far beyond what is required. This also applies to a specific group such as the
shareholders of a company, as what they believe to be right (i.e. the notion that the sole
responsibility of the company is to maximise their wealth) is not acceptable by the rest of
the society.
The notion of how the conscience is unique from individual to individual leads to a
discussion of morality and relativism.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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3.1.3. Relativism
The extreme case of relativism in connection with ethics is what Freeman & Gilbert
(1988) refer to as naive relativism. Naive relativism builds on the facts that moral
decisions are very personal, very serious and very complex. Hence it becomes hard, if not
impossible, to judge people and organisations on their ethical decisions. The next level
broadens the term relativism to hold that different cultures have different moral standards
(cultural relativism)9. These standards simply incorporate the desires of the people in a
set of moral standards, so that the desires are satisfied (Beauchamp & Bowie, 2001). The
morality varies from culture to culture, and cultural relativism therefore points to the
difficulty of prescribing what is wrong or right. Extending the notion of relativism even
further, ethical relativism is a normative proposition stating that whatever a certain
culture thinks is right or wrong really is right or wrong for members of that culture
(Beauchamp & Bowie, 2001). This means that if e.g. bribery is accepted in a culture it is
not wrong to engage in contracts that use bribery. And not only is it accepted to act in
accordance with a culture’s moral standards, it is in fact obligatory for members of that
culture to do so (Bowie in Freeman & Werhane, 1997). So as opposed to naive relativism
and cultural relativism, ethical relativism actually prescribes what is right and wrong,
whereas the first two simply points to the differences between people/cultures.
Beauchamp & Bowie (2001) do, however, criticise cultural and ethical relativism. First of
all, differing opinions on how to live life are not necessarily a sign of completely
different perceptions of ethics between cultures. A universal set of ethical standards
seems to exist - however broad it may be. These standards serve to prevent total chaos in
the world, but do not prescribe rules for business. What is important to remember is that
if relativism is accepted the whole discussion of ethical/unethical and moral/immoral
would be obsolete. This is obvious from the point of view that unethical would simply be
justified as “difference in culture”. Especially the notion of naive relativism would result
in making it impossible to judge the actions of others, and even yourself, as there would
9 See Freeman & Gilbert (1988) for a discussion of other levels of relativism such as role relativism and social group relativism. Both of these have much in common with naive and cultural relativism, and will therefore not be described in detail here.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
14
be no right or wrong. It is also important to remember that different people as well as
cultures may very well learn from each other. This implies an emerging understanding of
basic notions of right and wrong and would help explain why e.g. cannibalism is no
longer accepted in cultures where it was previously customary. Another example is,
again, bribery; as the developing nations of the world advances, bribery has become less
respected and this could be the result of a common understanding of ethics. Therefore,
today some notion of basic morality and ethics must be perceived to be universal.
3.2. Ethics and business
The discussion of morality and ethics in society is of great importance in relation to ethics
and morality in business. The dilemma of whether a corporation can be expected to be
morally responsible for its actions, or if the only responsibility of a corporation is to
maximise profits and value for its owners is again at the very centre of interest. From
Friedman’s, Smith’s and to some extent Jensen’s points’ of view the latter is true, whilst
many others strongly disagree with them. One dominant opponent of the classical writers
is Freeman (e.g. 1984, 1988).
“We must put ethics in its rightful place at the very center of discussions about corporate
strategy.”
Freeman & Gilbert, 1988, p. 7.
This is just one example of the opponents of shareholder capitalism. There are several
reasons for the increased focus on morality and ethics in business. One such reason is,
that as corporations have grown in size and power since the industrialisation, the fear of
these companies has also increased. With several of the world’s multinational companies
having grown to exceed the economic value of the smaller nations of the world, ethical
behaviour on behalf of the companies is more urgent than ever. These companies are thus
expected to be responsive to all their stakeholders and implement ethical strategies
regarding the management of the company.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
15
3.3. Corporate social responsibility
Extending the notion of corporate ethical behaviour introduced in the previous section
leads to the introduction of corporate social responsibility (CSR). Whereas business
ethics deals with issues of right and wrong, CSR specifies more accurately what is
expected of a corporation. Still, ethics forms a significant part of the foundation of CSR.
One definition of CSR is:
“… a concept whereby companies integrate social and environmental concerns in their
business operations and in their interaction with their stakeholders on a voluntary
basis.”
European Commission, 2001, p. 8.
A key word in the quote from the European Commission’s green paper on CSR (2001) is
“voluntary”. As this implies for a company to be socially responsible, it is not enough to
merely comply with the law. The European Commission (2001) gives a number of
reasons for the increased focus on CSR. These include increased awareness of, and
concern about, the environment; increased transparency of business activities due to
information and communications technology; new and escalating concerns from various
stakeholder groups as a result of globalisation and finally increasing company size.
Although they call for more focus on CSR the Commission acknowledges the fact that
the primary objective of a corporation is to generate profits. If it was not so the
corporation would not be able to contribute positively to society and environment. This
corresponds to the perception that corporate obligations include providing goods and
generating profits. Besides this economic responsibility the company has a legal
responsibility, meaning that it must obey the law. The third responsibility is ethical. The
ethical responsibility goes beyond the law in the sense that it is not always enough to
simply obey the law. Finally, for a company to be socially responsible it has a
discretionary/philanthropic responsibility (Freeman & Werhane, 1997). This
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
16
responsibility includes donations to various charitable causes, local improvement projects
etc10.
Aside from the pure responsibility aspect of this discussion, the European Commission
(2001) goes on to argue that there might be an economical benefit for companies that are
socially responsible; an aspect ignored by many. In the discussion of morality, ethics and
business, economic aspects are generally negative. That is, negative in the sense that
acting in an ethically correct way may be associated with additional costs as opposed to
behaving unethically. Behavioural improvements that may lead to economic gain include
new customers because of a good reputation, more loyal employees, increased respect
from suppliers and distributors etc. How much a socially responsible firm can expect to
benefit is difficult to say, but the Domini 400 Social Index (DSI)11 has consistently
outperformed the S&P 500 since its introduction in 1990 (European Commission, 2001).
It is, however, important to note that it is very difficult to determine how much of the
success of these companies can actually be ascribed to their responsible behaviour. One
objection to this link between CSR and financial performance could be that management
of these companies is simply more attentive to detail and more in sync with what is going
on in the business environment. Another argument could be that financially strong
companies tend to become socially responsible as a result of their success and not
successful as a result of their socially responsible management style.
With the DSI being modelled on the S&P 500, approximately 250 of the 400 companies
in the index are also included in the S&P 500. And it seems very likely that the top
performers on both indexes are in fact the same companies. KLD list companies such as:
Johnson & Johnson, Intel, Merck and Microsoft as some of the top ten holdings of the
DSI. These four companies were also among the top ten holdings of the S&P 500 in 2002
10 A detailed discussion of corporate philanthropy will not be included as this is of little relevance to the objective of the thesis. 11 Domini 400 Social Index is a benchmark developed by KLD Research and Analytics which is used to measure the impact of social responsibility on financial performance (www.kld.com/benchmarks/dsi.html). KLD Research and Analytics, Inc. is an investment consultancy that strives to promote globally socially responsible investing. There are a number of other social and ethical indexes in the US in particular; DSI, however, is the first of its kind.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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(www.standardandpoors.com). Of course there are differences, mainly with companies
involved in e.g. weapons manufacturing, nuclear power, tobacco and alcohol not
available for selection in the DSI. Additionally, Svendsen (1998) argue that while good
deeds and corporate social responsibility might not always be rewarded by the stock
markets, companies that are irresponsible and unethical will certainly be punished. So if
improved performance is not a reason for managers to behave responsibly, then maybe
the fear of deteriorating performance in case of irresponsible behaviour might be.
Another problem is determining if a company is in fact socially responsible. Though
many have tried it seems very hard to objectively determine what social responsibility is
and also measure it. Clarkson (1995) performed more than 70 case studies over a period
of ten years and found it problematic to determine if a company’s social performance was
satisfactory. According to Stanwick & Stanwick (1998) many different relationships have
been used and tested, including annual reports issues, pollution, questionnaires to CEOs,
philanthropy and a combination of more of the above and others as well. This lack of
standards for measuring socially responsible behaviour complicates research which is
probably also one of the main reasons why the European Commission (2001) have called
for more research on corporate social performance and financial performance in
particular.
Trying to clarify towards whom companies have a responsibility towards can be
somewhat difficult. Depending on who answers this question, the reply might be either
shareholders or stakeholders. Both terms have been introduced, but the description of
stakeholder theory is still only superficial.
4. Stakeholder theory
The introduction of stakeholder theory wraps up the progress from ethics in general, via
ethics in business and CSR to a management strategy. In that sense stakeholder theory
strives to show how to implement ethics and CSR in the organisation, while also
extending the areas of corporate responsibility somewhat further.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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A stakeholder in an organisation is any group or individual who can affect or is affected
by the achievement of the organisation’s objectives
Freeman, 1984, p. 46.
This definition is the most commonly used definition of a stakeholder. Freeman himself
quotes Stanford Research Institute (SRI) as the first to mention the term stakeholder in an
internal memo from 1963. SRI defined stakeholders as those groups without whose
support the organisation would cease to exist (Freeman, 1984). Others have used the term
between 1963 and 1984, but Freeman’s definition has become the most widely cited, he
is also one of the most well respected researchers on the subject. Besides his book
“Strategic Management: A stakeholder approach” from 1984 he has published numerous
articles and books, many in collaboration with other researchers.
4.1. Emergence of the stakeholder society
According to Freeman (1984) the view of the corporation as such has developed over
time. Corporations have evolved from a rather simplistic view via a more complex one
and finally to the stakeholder view. The first and most simple view is what he refers to as
the production view. At this stage, business was simply to buy raw materials and
transform them into products which were then sold to customers (see Figure 2)
Figure 2: Production view of a company
Source: Freeman (1984)
This was (and maybe still is) mostly the situation for small, entrepreneurial or family
owned businesses. Those companies may very well have grown in size, but their
perception of the task at hand has not changed. Outside of their own niche there is an
Suppliers Company/Mgmt.
Customers
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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environment with which they have very little interaction, thus the importance of this
environment is minimal. Gradually new interest groups emerged and the view of the firm
became somewhat more complex. This second view, which Freeman refers to as the
managerial view, includes owners and employees (incl. unions) along with suppliers and
customers. The managerial view emerged because of the separation of ownership and
control and the increasing influence of the workforce. Besides being more complex in the
sense of more players the model also transforms the relationship between players into
being reciprocal (see Figure 3). Consequently, more interaction occurs among the
different groups.
Figure 3: Managerial view of a company
Source: Freeman (1984)
As the influence from the outside environment increases, Freeman’s view of the company
develops further. This results in the emergence of the stakeholder view of business. In a
modern business society it is not enough to just look at the corporation from the
managerial point of view; there are many other groups besides suppliers, customers,
owners and employees that are of great importance to the company. As mentioned these
stakeholders are those who can affect or are affected by the actions of the company. The
Suppliers Company/Mgmt.
Customers
Employees
Owners
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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increase in number of stakeholders materialises from increased pressure from, and
dependence on, the outside environment. This results in a number of participants
interacting bilaterally with the company (or at times multilaterally among each other and
the company). Donaldson & Preston (1995) point out that no priority of one set of
interests prevails over another, i.e. the company’s interests are not more important than
an individual stakeholder group’s. Besides the four groups from the managerial view,
many others including media, consumer advocates, competitors, environmentalists etc.
are important (see Figure 4).
Figure 4: Stakeholder view of a company
Source: Freeman (1984)
When studying Figure 4 some stakeholders are more important in the short term, whereas
others may only matter in the long run and rarely affect the actions of a manager.
Company/Mgmt.
Envir-onmen-talists
Sup-pliers
SIGs
Consu-mer adv.
Owners
Local commu-nity
Govern-ments
Media
Compe-titors
Custo-mers
Em-ployees
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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Nevertheless, they must all be considered and cared for. Shareholder wealth
maximisation in its purest form fails to recognise the long term effects that the actions of
e.g. special interest groups (SIG), local communities and environmentalists may have on
a company. It thus merely regards such groups as obstacles to success. Freeman argues
that by being responsive to the needs of all these groups a company will provide itself
with a competitive advantage in the form of its good relationships. This advantage may
not be obvious in the short run, but in the long term it may turn out to be crucial for the
existence of the company. That conclusion partly corresponds with that of Jensen (2001)
in the sense that it looks at the long term effects. Freeman argues that companies ought to
be attentive to the stakeholders because it is the right thing to do ethically, but he also
holds that being responsive to the needs of the stakeholders may in fact benefit the
company in many ways. This should provide the companies with an incentive to do so of
voluntarily, without the intervention of the legislative power.
4.2. Voluntarism
An important aspect of stakeholder theory is the concept of voluntarism. Freeman (e.g.
1984, 1991) states that it is important that the individual corporations adopt a stakeholder
orientation by themselves (voluntarily) and that they are not forced by e.g. government
pressure and legislative changes. He even holds that if a stakeholder problem is resolved
by a government agency or the court system it must be seen as managerial failure. This
corresponds to the quote from the European Commission in section 3.3 on CSR. Evan &
Freeman (1988) do, however, acknowledge that legislation may have to play a role in
defining stakeholder rights and claims. Evan & Freeman (1988) continue to point out the
importance of corporate initiatives and voluntary adaptation to the stakeholder view,
mainly in form of advisory boards and stakeholder representation on the board of
directors etc. This way legislation can support management’s own initiatives. By
voluntarily adapting to the stakeholder society, companies implicitly acknowledge that it
is not only the shareholders that have rights in regards to the company.
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4.3. Stakeholder theory and property rights
Stakeholder theory furthermore redefines the view of property rights in connection with
corporations. Instead of the traditional view introduced in section 2 that the owners are
entitled to the profits of the company, the focus of stakeholder theory leans more towards
the rights of all concerned parties. This means that each stakeholder has property rights as
a consequence of the individual’s input; consequently the general conception that private
property exclusively concerns the owners is questioned (Donaldson & Preston, 1995).
Freeman & Phillips (1999) mention the employees’ rights to their labour, the consumers’
rights to their wealth and the communities’ rights to public goods. When viewing
property rights in this fashion it is again obvious that a company must respect the
individual stakeholder’s property rights, hence respect all stakeholders12.
After describing how Freeman (1984) sees the business environment as having evolved
into a stakeholder society, it is highly relevant to look at how this change has in fact been
justified. Is stakeholder superior to the traditional shareholder capitalistic view – and
how?
4.4. Justification of stakeholder theory
The argument that the business world has changed and that managers, therefore, must be
responsive to all stakeholders is just one opinion. Since it is merely an observation, a
change in management style from shareholder to stakeholder focused is not yet justified.
Freeman (1984) also recognises that he is presenting his bid for a management theory in a
changing world, and that it is not yet empirically tested and justified (at the time of
writing). He intends to leave the justification to others, but the body of literature and
surveys on the subject is very varied in regards to form and quality. According to
Donaldson & Preston (1995) a great deal of empirical research exists on CSR, but the
work regarding stakeholder theory is very limited. They state that the rather large amount
12 Donaldson & Preston (1995) mention Coase, Honore and Pejovich as good sources for background information on the discussion of property rights.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
23
of theoretical literature on the subject justify and explain CSR in many different, and at
times contradictory, ways.
Pointing out the confusion that may occur when studying the stakeholder theory,
Donaldson & Preston (1995) divide the literature into three different approaches:
descriptive, instrumental and normative13.
The descriptive thesis of stakeholder theory focuses on describing how an organisation is
a constellation of competing and cooperating stakeholders. It can also be used to
investigate if the stakeholders perceive the company as such a constellation, or simply to
determine which type of management strategy a certain company adopts.
The instrumental thesis of the theory links profitability to the adoption of a stakeholder
focused management style. Hence, it compares stakeholder focused firms with e.g.
shareholder value maximising firms based on measures such as profitability and growth.
Finally, the normative approach to stakeholder theory is very much in line with the
discussion on business and ethics in see section 3.2., Kantian ethics in section 3.1.1. and
CSR in see section 3.3. The basic idea is thus that a corporation has an obligation to treat
its stakeholders well and not only because such actions might help increase shareholder
wealth.
Donaldson & Preston (1995) visualise the different aspects and uses of stakeholder theory
as layers in a model (see Figure 5). This figure also highlights the importance of the
normative aspect as this is pictured as the centre, or core, of the whole theory. Arguably,
the instrumental thesis is of more importance to many companies and especially their
owners, as this is the aspect that may help point to the superiority of stakeholder theory
over other models from a financial point of view.
13 This is closely linked to the different approaches to ethics described in section 3.1.1.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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Figure 5: Uses of stakeholder theory
Source: Donaldson & Preston (1995)
The purpose of the Donaldson & Preston (1995) paper is two-fold. Firstly, they strive to
set up a framework for dividing the different contributions to stakeholder theory. This
takes the form of Figure 5 as described above. Secondly, they want to determine if some,
or all, of the three aspects are empirically justifiable. They have not tested the different
hypotheses themselves, but instead they analyse and evaluate various contributions of
other researchers. The following section is therefore based on their literature survey, but
not limited to their findings.
4.4.1. Descriptive justification
Descriptive justification mainly comes down to researchers pointing to a trend of
management tendencies to adopt a stakeholder approach or not. As a consequence of his
problems with determining if a company is socially responsible, Clarkson (1995) turned
to a more stakeholder based research style. Holding that the term stakeholder is more
accessible and easily defined than social performance he performed a very detailed study
of more than 70 companies over a span of 10 years as mentioned in section 3.3.
Donaldson & Preston (1995) acknowledge that a significant number of the companies
Descriptive
Instrumental
Normative
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
25
researched by Clarkson were stakeholder oriented. Another observable trend is
legislative changes. Donaldson & Preston (1995) point out a trend in the U.S. legislation
and statutory law that weakens management’s capacity for focusing solely on increasing
shareholder wealth. This trend is also observed, perhaps to an even greater extent, in
Europe and Japan.
Donaldson & Preston (1995) do, however, dismiss the descriptive hypothesis of
stakeholder theory because they do not acknowledge it as empirically justifiable. They
argue that both management surveys and legal developments are merely simple facts, and
that those facts do not provide stakeholder theory with the proper support to justify it as a
successful management strategy. They also point out that although there may currently be
a significant number of stakeholder focused companies this does not prove that
stakeholder theory is superior – it only proves that it is more popular. It does,
nevertheless, seem as if Donaldson & Preston (1995) might dismiss the descriptive thesis
rather easily. It is correct that just because the trend leans towards stakeholder theory, it
does not necessarily imply that this approach is better, but it seems as if they fail to
acknowledge that it may be true. One reason for the increased focus on stakeholder
theory could be its superiority. Nevertheless the fact remains that a purely descriptive
approach to stakeholder theory does not prove anything else than the degree of support
the theory enjoys, and only points out current trends in management and legislation. This
may also be the likely reason why other authors such as Freeman & Phillips (1999) have
left out the discussion of descriptive justification and focused on the normative and
instrumental theses described next.
4.4.2. Instrumental justification
The gap that the descriptive justification leaves between the facts and the reasons behind
them is attempted explained by the instrumental approach. The instrumental approach
strives to connect stakeholder theory with superior financial performance. The process of
trying to justify the instrumental thesis is thus concerned with two issues. First, it is
essential to separate stakeholder oriented companies from non-stakeholder ones. Second,
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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these two groups must be compared to prove or disprove the hypothesis that companies
adopting stakeholder principles and practices perform better than those neglecting to do
so.
Clarkson (1995) as well as Donaldson & Preston (1995) state that there is very little
research available regarding the instrumental hypothesis. Both papers point to the fact
that the results of the large body of literature about corporate social and financial
performance are not necessarily applicable to stakeholder theory. The terms stakeholder
theory and social responsibility are not substitutable. Therefore the results of the
performance studies of the two areas cannot be expected that are so either. Clarkson
(1995) focuses more on how to find a measure for corporate social performance based on
stakeholder theory than on linking stakeholder theory with financial performance. One of
the criteria he uses for a firm to be successful is therefore financial gain rather than
setting financial gain as the objective itself. Therefore the results of Clarkson’s (1995)
analysis of the instrumental thesis are questionable in the sense that the arguments are not
instrumental.
Donaldson & Preston (1995) also argue that the instrumental thesis is not analytically
valid either. Their reason for dismissing it from an analytical point of view is, that it is
rarely justified based on instrumental arguments. Parts of the analytical arguments are
nonetheless instrumental, e.g. the notion that efficiency in managing the stakeholder-
agency problem will result in better performance. The stakeholder-agency problem is
quite similar to the principal-agent problem in section 2, only different in the sense that
there is not only a conflict of interest between management and the owners; it is instead
to be found in the relationships between management and all stakeholder groups.
Naturally this complicates matters, especially when it comes to setting up an incentive
system to align management’s preferences with those of the stakeholders14. Charreaux &
Desbriéres (2001) argue that managing those relationships efficiently will result in
14 For a more detailed discussion of stakeholder-agency theory see e.g. Tirole (2001), Hill & Jones (1992) or Charreaux & Desbriéres (2001). Focus here will be more on the notion of efficiency than the discussion of stakeholder-agency problems in itself.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
27
improved performance. This corresponds to the analytical argument for the instrumental
approach to stakeholder theory. In a much similar fashion efficiency is at the centre of
interest when discussing the idea of a company consisting of a number of contracts with
the various stakeholder groups (e.g. Evan & Freeman, 1988, 1990). These contracts must
be managed efficiently for the company to perform optimally. This implies that the
relationship with the stakeholders must be actively managed in order to maximise the
wealth of all parties implicated.
Those attempting to defend the instrumental thesis of stakeholder theory continuously
turn to non-instrumental arguments (Donaldson & Preston, 1995). They claim that the
shift from shareholder focused management to stakeholder focused will fundamentally
have to be based on something else than instrumental arguments. While they are right that
most contributors to this field have (to a greater or lesser extent) pointed to terms such as
“morally right”, “fair” and “social responsibility”, they fail to acknowledge that
companies nowadays may shift focus based on other reasons. It seems fair to assume that
as stakeholder theory slowly gained popularity, the companies that started adopting this
style of management could not have been aware of the economic consequences. But as
the popularity increased, managers who adopted the approach started believing that it was
not just the right thing to do from a moral standpoint, it may also be the right thing to do
economically. As Donaldson & Preston (1995) themselves acknowledge that the
instrumental justification does not necessarily have to be empirically tested it seems that
they dismiss the instrumental justification a bit too easily.
Berman, Wicks, Kotha & Jones (1999) have made a rare attempt to empirically test
stakeholder theory. They primarily focus on the instrumental thesis as this is a neglected
area of empirical analysis. If the instrumental thesis is valid, then the conflict between
shareholder capitalism and stakeholder theory no longer ought to be an issue. There
would then be harmony between the two opposing theories in which case Friedman’s
(1962) notion that the only responsibility of a company is to maximise profits (see section
2) would be fulfilled via implementing a stakeholder approach in the company.
Stakeholder focused management is thus seen as a part of corporate strategy, but not as
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
28
the driving force of it. This leads to Berman, Wicks, Kotha & Jones’s (1999) definition of
what they call the strategic stakeholder management model15, which states that managers
will attend to stakeholders’ interests as long as they can affect the company’s financial
performance.
Using KLD data combined with financial and various other data Berman, Wicks, Kotha
& Jones’s (1999) test their hypotheses on 81 of the top 100 of the fortune 500 companies
over a period of six years from 1991 to 1996. They further decid to include measures of
firm strategy and operating environment, hereby attempting to separate the effects of
various stakeholder relationships from those of business environment and general
strategy in order to provide better support for the theory (or dismiss it). Those measures
are approximated from the data collected. They subsequently test the model with the
dependent variable being return on assets (roa). Out of the five stakeholder relationships
examined (Employees, natural environment, workplace diversity, customers and product
safety, community relations) only two directly affect financial performance. Those two
are employees and product safety/quality, whereas the other three were found to only
have an indirect effect on firm financial performance. Berman, Wicks, Kotha & Jones
(1999) are however reluctant to dismiss the importance of the last three stakeholder
relationships. The reason why natural environment does not have a direct effect could be
that it is very industry specific how much attention needs to be paid to it. Regarding
workplace diversity and community relations Berman, Wicks, Kotha & Jones (1999)
point to geographic differences as one reason why they do not directly affect financial
performance.
The use of the term stakeholder in Berman, Wicks, Kotha & Jones (1999) nonetheless
seems a bit off target. They mention Freeman (1984) and Donaldson & Preston (1995) as
their main influences, but fail to effectively use their definitions of stakeholders. The
reason for this is quite likely the use of the KLD index. KLD focuses very much on social
responsibility; and CSR is not the same as stakeholder theory. This is seen in the failure
15 Berman, Wicks, Kotha & Jones (1999) do not limit their study only to the strategic stakeholder management model. It is however the proposition of the most interest to this thesis.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
29
to include what many see as important stakeholders, i.e. owners, suppliers and
management. In that sense the study is a study of CSR every bit as much as one of
stakeholder theory. On the other hand they do focus on the influences of the individual
stakeholders and not just on a total measure of social responsibility. Despite the weakness
of the KLD data, its major strength lies in the continuous collection of data and extensive
research. Furthermore, the inclusion of several measures regarding strategy seems to
complicate matters, although it does serve a purpose in the eyes of the authors. By using
roa as their measure of profitability Berman, Wicks, Kotha & Jones (1999) limit
themselves to the use of accounting numbers only. This means that there is neither a
measure that concerns the value generation for the owners nor one that includes the
market value of the company. Nevertheless, as Harrison & Freeman (1999) point out, this
study is one of the best of its kind and also one of the only ones available.
Focusing more on value generation for the shareholders, Tiras, Ruf & Brown (1998) used
the KLD data to measure the effect of stakeholder oriented management on valuation
coefficients and earnings. They rated the individual firms’ stakeholder performances and
ranked them as good, neutral or bad and then tested their hypothesis on 401 companies
over a period of five years. They found that customers, environment and employees have
an effect on both performance measures. Their study suffers from the same weaknesses
regarding the KLD data, and neither Tiras, Ruf & Brown (1998) nor Berman, Wicks,
Kotha & Jones (1999) seem to test how the different stakeholder groups work in
collaboration with each other.
4.4.3. Normative justification
Donaldson & Preston (1995) based their dismissal of the instrumental thesis on the fact
that, ultimately, normative reasons are used to justify the theory. Their main argument for
stakeholder theory being fundamentally normative is that the alternative, shareholder
capitalism, is morally unacceptable. The arguments for the normative justification are
based on ethics, morality, utilitarianism, corporate social responsibility etc. Another point
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
30
is that of property rights not being exclusive for the owners of the company. This is the
main point emphasised by Donaldson & Preston (1995), while Freeman & Phillips (1999)
also point to the fact that property rights for all stakeholder groups result in management
being obligated to paying attention to stakeholders from a normative point of view. It is
thus what management “ought” to do, and should do in order to respect the individual
stakeholders. This leads to the conclusion that:
“The stakeholder theory is fundamentally normative.”
Donaldson & Preston, 1995, p. 12
After outlining the different attempts to justify stakeholder theory from different aspects
an interesting question arises, namely: who are the relevant stakeholders?
4.5. Stakeholder identification
All writers within the area of stakeholder theory have a definition of stakeholders.
Nevertheless, the definition is often not clear and at times it is only stated implicitly.
Some contributors just mention various stakeholder groups (e.g. Agle, Mitchell &
Sonnenfeld, 1999) and others state the criteria which they believe form the basis for
separating relevant from non-relevant stakeholders (e.g. Donaldson & Preston, 1995).
In its broadest definition, the term “stakeholder” includes basically any group or
individual whose situation or actions are even remotely affected by the company and vice
versa. This is what Evan & Freeman (1988) refer to as the “wide definition” of a
stakeholder (quoting Freeman and Reed, 1983). Furthermore, Mitchell, Agle & Wood
(1997) claim that companies can be vitally affected by, or vitally affect, almost anyone,
thus resulting in an extremely broad definition of the term stakeholder. At the other end
of the spectre some writers only acknowledge a few groups such as shareholders,
customers and employees as stakeholders (e.g. Cornell & Shapiro, 1987). Therefore it is
important to find a method for separating legitimate stakeholders from illegitimate (or
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
31
significant from non-significant). Whether a stakeholder is legitimate or not is determined
by the stakeholder’s ability to affect the direction of the company (Freeman, 1984). This
means that the company must concede to spending time on satisfying any stakeholder
group with this ability, whether or not the claim itself seems legitimate to the company.
Thus, a stakeholder may have an illegitimate claim and still be legitimate. This leads
directly to Freeman’s definition that stakeholders are those who can affect or are affected
by the company’s actions; it also corresponds to Evan & Freeman’s (1988) “narrow
definition” (quoting Reed & Freeman, 1983). Mitchell, Agle & Wood (1997) define the
groups within the “narrow definition” of the term stakeholder to be those with a direct
relevance to the firm’s core economic interests. It is this “narrow definition” of a
stakeholder that is of the most interest to managers and researchers alike, whilst it is also
important not to forget the existence of the “widely defined” stakeholders, who may gain
influence, importance etc. over time, thus advancing into the “narrow definition”.
Clarkson (1995) has a somewhat different way of dividing stakeholders into groups. He
focuses on primary and secondary stakeholders. The primary stakeholders are those
whose continuing participation the corporation cannot survive without. This is not quite
like the “narrow definition” or the general definition of stakeholders held by Freeman.
Clarkson’s definition deals with the actual survival of the company whereas Freeman
more moderately focuses on the ability to affect. On the other hand Freeman’s definition
corresponds very much with Clarkson’s definition of secondary stakeholders. Secondary
stakeholders are those who influence or affect the company and vice versa. In this manner
Clarkson makes a more narrow definition of what he sees as the most important
stakeholder groups than Freeman etc. have done before him. Appendix 1 includes a
section on who various authors acknowledge as stakeholders16.
16 Appendix 1 also briefly outlines the research of the most relevant authors.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
32
Furthermore, Figure 6 can help show the relationship between the different terms used
above.
Figure 6: Definitions of stakeholders
What Freeman (1984), Evan & Freeman (1988) and Clarkson (1995) have in common
though is the fact that the stakeholders are divided according to the individual writer’s
personal perception of their relative importance. There is no consideration of individual
companies, lines of business, country, culture etc. Clarkson (1995) does, however,
mention that those groups he includes in his primary and secondary stakeholder groups
are the only typical ones. But just as Freeman (1984) and Evan & Freeman (1988) he
does not discuss how and why some groups may vary in importance and influential
power.
4.5.1. Identification typology
From the perhaps broadest possible definition of the term stakeholder put forth by
Freeman (1984) to the various attempts to specify stakeholder groups there is still very
little consistency when it comes to identifying stakeholders. So narrowing the range of
stakeholders requires applying some acceptable and justifiable sorting criteria to the
selection of stakeholder candidates (Mitchell, Agle & Wood, 1997). While pointing out
that the narrow view of the stakeholder is often associated with a legitimate claim on the
company, Mitchell, Agle & Wood (1997) also warn that “wide” stakeholders may have
the power to influence (even without a legitimate claim). Thus, legitimacy and power are
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
33
the two main attributes when it comes to identifying which stakeholders are relevant to
the managers. But according to Mitchell, Agle & Wood (1997) those two attributes alone
are not sufficient, and they emphasise that urgency is also of great importance. There is
very little research available on how to identify the stakeholders that are truly important
to managers (Harrison & Freeman, 1999) and the work of Mitchell, Agle & Wood (1997)
is one of the most important contributions to this part of stakeholder theory. This, and the
importance of being able to clearly identify relevant stakeholders, justifies an elaboration
of the three attributes: power, legitimacy and urgency.
Power may be tricky to define, but not that difficult to recognise (Mitchell, Agle &
Wood, 1997). Constructing a definition based on the previous attempts of other writers17
Mitchell, Agle & Wood (1997) conclude that a party to a relationship has power if and
when it can impose its will in the relationship. This means that in some cases this party
may even make other parties of the relationship do something they would otherwise not
have done. It is, however, important to note that power is not necessarily something a
party will have forever; power can be gained and lost.
Legitimacy is based on the discussion of morality and ethics (see section 3.1.). It springs
from what Donaldson & Preston (1995) call normative justification (section 4.4.3.)
meaning that whether or not a claim by a stakeholder is legitimate is based on what is
“right”. This implies that if the actions of a certain stakeholder are proper, responsible
and desirable within the norms and rules of that particular society, this stakeholder will
appear legitimate to society, the company and the other stakeholders (Mitchell, Agle &
Wood, 1997). A legitimate stakeholder is nonetheless not always powerful, just as a
powerful stakeholder is not always legitimate.
Adding to those two attributes, Mitchell, Agle & Wood (1997) aim to capture the
dynamics of stakeholder-management relationships by introducing urgency as the third
and final attribute. As mentioned above, power as well as legitimacy can change over
17 E.g. Weber (1947) , French & Raven (1960) and Salancik & Pfeffer (1974)
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34
time; neither is everlasting, at least not without an effort on behalf of the stakeholder. A
stakeholder may have a legitimate claim, be powerful, or maybe even both without the
claim being urgent. Urgency is the degree to which stakeholder claims call for immediate
attention and is thus based on both the time-sensitivity of the claim as well as the
criticality. If a claim is very time-sensitive and of critical importance, it becomes urgent.
Urgency may previously have been recognised as an implicit part of power and/or
legitimacy, but separating it from the other two attributes adds to the explanatory power
of the typology.
4.5.2. Stakeholder classes and salience
After introducing the three attributes for identifying relevant stakeholders, it is interesting
to look at what consequences the existence of one or more attributes have on the way
managers perceive the stakeholders. The salience of a certain stakeholder is the degree to
which managers give priority to that stakeholder (Mitchell, Agle & wood, 1997). Hence,
a stakeholder has a high salience if managers prioritise that stakeholder highly and a low
salience if it is not regarded as high priority. The degree of salience again depends on the
combination of the three attributes: power, legitimacy and urgency. One of the attributes
alone is often not enough to yield high salience; a combination of two usually does
whereas the presence of all three virtually guarantees a very high salience with managers.
Thus stakeholder salience is positively related to the accumulative number of attributes.
After acknowledging the three types of attributes, Mitchell, Agle & Wood (1997) set up
different classes of stakeholders depending on the number of, and which, attributes the
stakeholder possess. As can be seen from Table 1 the three main groups are latent
stakeholders, expectant stakeholders and definitive stakeholders. The first two of these
are again divided into three sub-classes, all of which will be briefly described.
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Table 1: Stakeholder classes
Latent stakeholders are often not given much attention as they only possess one attribute;
i.e. they have a low salience. Dormant stakeholders are those that only possess the power
to influence the firm, but do not have a legitimate or urgent claim on the company. They
have little interaction with the company and no real interest in using their power (though
it is not always so). Discretionary stakeholders are those with a legitimate claim, but
nothing more. With neither urgency nor power these stakeholders can do very little to
influence companies and management is subsequently not forced to pay much attention to
them. This group, nevertheless, receives some attention as various groups within the
discretionary stakeholder group are recipients of corporate philanthropy due to their
legitimate claims (Mitchell, Agle & Wood, 1997). Finally, the demanding stakeholders
are those with only urgency to backup their claim. Without power and legitimacy this
group of stakeholders has very little effect, besides the ability to irritate and annoy.
Therefore management will rarely pay much, if any, attention to this group. Although
latent stakeholders are rarely given much attention they should not be forgotten totally
either. As mentioned previously the dynamism of the stakeholders’ positions may lead to
latent stakeholders obtaining another attribute, thus becoming more salient and requiring
more attention.
Number of attributes
Class Sub-class Attributes
1 Dormant Power
1 Discretionary Legitimacy
1
Latent stakeholder
Demanding Urgency
2 Dominant Power, Legitimacy
2 Dependent Legitimacy, Urgency
2
Expectant stakeholder
Dangerous Power, Urgency
3 Definitive stakeholder Definitive Power, Urgency, Legitimacy
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Expectant stakeholders possess two of the three attributes in any given combination. This
makes them moderately salient. As opposed to the passive nature of the latent
stakeholders expectant stakeholders are typically more active. The increased activity on
behalf of the stakeholders results in managers being more attentive to this group of
stakeholders. Dominant stakeholders have a legitimate claim and the power to push it
through. Through those two attributes the dominant stakeholders will always have
influence on the company and the managers will always pay attention to them. This is the
group that is typically seen as the stakeholders that “matter” to managers. They are
definitely part of the narrow group of stakeholders (Evan & Freeman, 1988) and very
much correspond to the definition of primary stakeholders used by Clarkson (1995) in the
sense that they can be vital to the company’s survival. Mitchell, Agle & Wood (1997)
mention such phenomena as outside board representation, the existence of human
resource departments and public affairs offices as signs of those stakeholder groups being
dominant. When a stakeholder has an urgent and legitimate claim this stakeholder
becomes dependent. This group of stakeholders depend on other stakeholders to provide
the power to make management pay attention to their claims. As management is not
forced to deal with the dependent stakeholders due to the lack of power of this group, the
dependent stakeholders may often be neglected. The final group within the expectant
stakeholders is dangerous stakeholders. This group has an urgent claim and the power to
affect the company which results in it being labelled as dangerous. With their demands
not being legitimate, thus not rightful, the problem is that they may force a company to
act in ways that it ought not. It is therefore important for managers to identify this group
of stakeholders before they decide to take action. In this way it may be possible to curb
the unjust demands by attempting to remove either the urgency or power. But while
identifying and possibly countering those groups it is important not to acknowledge them,
since this may just lead to more such groups emerging (by holders of urgent claims
striving for power or vice versa).
Finally, the highly salient stakeholders possessing all three attributes are the definitive
stakeholders. The characteristics of this group are quite similar to those of the dominant
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stakeholders. Managers will already be aware of the dominant stakeholders, and the
additional attribute of urgency will only encourage managers to deal with them faster.
Mitchell, Agle & Wood (1997) acknowledge that their justification of the theory of “who
and what really matters to managers” is ultimately logical and theoretical. They are open
for critical evaluation of the attributes, knowing that there may be others that are as good,
or possibly better. It is also important to note that the individual manager’s values may
heavily influence his or her perception of the three attributes and salience, thus making it
complicated to generalise. Agle, Mitchell & Sonnenfeld (1999) used data from CEOs of
80 large US firms to test the model of Mitchell, Agle & Wood (1997). They accepted the
three attributes and did not change them or the definition of salience before sending
questionnaires to the CEOs18. The questionnaires were formulated so that it would be
possible to test a number of hypotheses that required testing. The hypotheses and results
concerned two main areas of interest19:
1. The three attributes (individually and cumulatively). They found that power,
legitimacy and urgency are all related to stakeholder salience. This implies that
managers acknowledge those three attributes as being important when they
prioritise stakeholder interests.
2. Stakeholder salience and corporate performance. The regression made did not
show any significant relationship between stakeholder salience and corporate
performance. This model therefore cannot prove that stakeholder focus is the best
way of achieving success on a conventional financial basis20.
Although the study by Agle, Mitchell & Sonnenfeld (1999) is very useful when it comes
to applying the model presented by Mitchell, Agle & Wood (1997) there are also a few
18 Questionnaires were sent to 588 of the 650 firms in the KLD index. The response rate was only 13, 6%, but the authors claimed that due to generally low response rates from CEOs this was acceptable. 19 Agle, Mitchell & Sonnenfeld (1999) tested four main areas of Mitchell, Agle & Wood’s (1997) theory, but two of those were very much focused on the behaviour and values of the individual CEO which is of little interest to this thesis. 20 Agle, Mitchell & Sonnenfeld (1999) used return on equity (ROE) and return on assets (ROA) as their measure for economical success.
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weaknesses. First of all, the connection between stakeholder salience and the three
attributes has only been tested for five stakeholder groups. Those groups are: customers,
employees, shareholders, government and communities. Another issue is the lack of
scrutiny of the attributes. In the original article Mitchell, Agle & Wood (1997) called for
criticism of power, legitimacy and urgency as the important attributes and they also
sought suggestions for alternatives. But even so, Agle, Mitchell and Sonnenfeld (1999)
rather silently accepted those attributes and conducted their studies based on them.
Having mentioned that, the usefulness of both studies should again be acknowledged, as
the purpose was to identify and test the attributes and salience, not which stakeholders are
important.
After reviewing the US based literature on stakeholder theory, including the instrumental
thesis and stakeholder salience, time has come to apply the theory to a study of
stakeholder theory in Denmark.
III. Empirical analysis
The purpose of the empirical analysis of this thesis is two-fold. Firstly, a group of
stakeholders, that is relevant for a study of stakeholder theory in Denmark, must be
defined. This initial part of the analysis is based on the framework of Mitchell, Agle &
Wood (1997) and is found in chapters 5 and 6. A discussion of how to decide whether or
not a particular stakeholder group is satisfied is included. Secondly, the instrumental and
to some extent the descriptive thesis of stakeholder theory is tested. The object is to
investigate if the implementation of stakeholder maximising measures leads to improved
and superior performance. This will be applied to a sample of 89 companies from seven
different industries listed on the Copenhagen stock exchange21. This central issue of the
analysis is found in chapters 7 and 8.
21 Selection of the sample is in section 7.4.1.
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5. Selection of stakeholder groups
Identifying stakeholders for an individual company, or possibly even a sector, may be
rather straightforward. Interviews and questionnaires are the most obvious ways of doing
so. But complications arise when it comes to identifying stakeholders across sectors and
companies. Some stakeholders will be important to one business, or company, and not all
that important to another. A generally accepted group of stakeholders must be sought, so
that it is possible to manufacture a set of standards applicable to different companies and
businesses. The importance of this generally accepted set of stakeholders is due to the
nature of the sample. A relatively precise identification may be achieved by focusing on a
specific sector or company, but trying to establish a generic group of stakeholders is more
interesting. Though a broadly applicable set of stakeholders will be identified, it is
important to bear in mind that the same set may not be applicable across different
countries and cultures. Differences between regions and countries may be significant, and
a different set of variables may therefore be required if the study is to be duplicated using
data from another culture.
Applying the Mitchell, Agle & Wood (1997) framework, focus will be on the definitive
and dominant stakeholders (see section 4.5.2.)22. This means that those stakeholders that
are vital for the company’s survival, i.e. the primary stakeholders (Clarkson, 1995), are of
the greatest interest. Including other stakeholders, especially the latent ones, would be too
complicated due to the diversity of the sample. Furthermore, an obvious reason for not
including latent stakeholders is the one presented by Mitchell, Agle & Wood (1997),
namely that managers rarely pay attention to this group. Regarding the other two groups
of expectant stakeholders (dependent and dangerous) it seems that urgency is somewhat
harder to define and measure, as it is in many cases specific for the individual company
or sector. Hence, dependent and dangerous stakeholders may in fact be latent
stakeholders to significant parts of the sample. The dependent stakeholders are thus not
22 As it is beyond the scope of this thesis to test the validity of the framework of Mitchell, Agle and Wood (1997, their contribution to stakeholder selection is accepted and applied.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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included due to the complexity of identifying urgency. Furthermore, dangerous
stakeholders are not included as managers should not succumb to their demands, only
strive to counter their actions. Focus will thus be on stakeholders with power and
legitimate claims on the company. This is also in line with Freeman’s (1984) emphasis on
legitimacy.
Previous studies have paid no, or very little, attention to the process of selecting which
stakeholders to include. As mentioned previously (section 4.5.2.) Agle, Mitchell &
Sonnenfeld (1999) only tested salience and the attributes for five stakeholder groups. A
study aimed at determining which stakeholders managers view as important would be
interesting, but is not included in this thesis. The same uninformed approach to
stakeholder selection is applied by Berman, Wicks, Kotha & Jones (1999). They select
five stakeholder groups without ever explaining why, and their selection furthermore
differs in several aspects in comparison to the more generally accepted stakeholder
groups (mainly by excluding managers, suppliers and owners). The selection of relevant
stakeholder groups below will be explained, but not empirically tested due to the sheer
scope of such an analysis.
5.1. Customers
Customers are included in the broadest (e.g. Freeman, 1984) as well as the narrowest (e.g.
Cornell & Shapiro, 1987) definitions of stakeholders as it can be seen from Appendix 1.
Companies exchange products/services for resources with the customers, who thus
provide essential revenue for the company. Customers form the absolute basis of
existence for the company. In this way they are essential to most other stakeholders, as
there would not be any discussion of stakeholders at all without the revenue from the
customers. Also, the customers are one of the groups found to have a direct effect on
financial performance (Berman, Wicks, Kotha & Jones, 1999, and Tiras, Ruf & Brown,
1998). Treating customers well with respect to good service and high quality, safe
products is the foundation of a successful business, as it is evident from stakeholder
theory as well as traditional management theory (e.g. Porter, 1980, 1984). Customers
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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have power in the form of free will to buy or not, and they have a legitimate claim as they
are right to expect safety, quality and service when they pay for a product.
5.2. Shareholders
Often owners’ needs are seen as contrasting the needs and interests of management and
other stakeholders. It does however not necessarily have to be so. Owners are an
important group of stakeholders that should never be neglected. The mere fact that they
own the company and have a financial stake in it justifies their importance. They are
entitled to a return on their investment, which has an effect on their livelihood (the
significance of this effect depends on the scale of the investment, the proportion this is of
total wealth, other income etc.). This constitutes a legitimate claim on the corporation,
and the owners furthermore posses’ power as well. The power of the owners lies in their
option to sell their shares (perhaps resulting in decreasing market value) and the power to
replace management (thus changing company strategy and policy)23. The owners should
therefore be perceived as an important stakeholder group and the failure to include them
in a stakeholder model could have severe consequences. Nevertheless, several
contributors to stakeholder theory have not included owners/shareholders as a stakeholder
group (e.g. Svendsen (1998), Berman, Wicks, Kotha & Jones (1999) and Tirole (2001)).
The reason for this may be that they implicitly assume that the claim that shareholders
have is not discussable, as they cannot be ignored. Another reason may be that they
simply do not acknowledge the claim of the owners on the same level as that of the other
stakeholders, thus implying that stakeholder theory and shareholder wealth maximisation
are two completely contradicting theories. Whatever the reasons, it is not justifiable if
common sense and the framework of Mitchell, Agle & Wood (1997) is applied.
23 Both of these examples of power can rarely be exercised by an individual shareholder. They are therefore most often a collective power, though not always so.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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5.3. Environment
The third stakeholder group is the environment. Some managers judge this stakeholder
group to be irrelevant to their business, possibly because they see it as lacking legitimacy.
Berman, Wicks, Kotha & Jones (1999) could not find support for the direct influence of
the natural environment on financial performance, but they did, however, not fully
dismiss the environment as a stakeholder group. Tiras, Ruf & Brown (1998) also found
the natural environment to have a direct influence on the market value of a company.
Focus here is on natural environment, but without dismissing the importance of the local
community. The environment has a legitimate claim on corporations in the sense that
managers must act to preserve the environment for themselves and future generations.
The immediate power of the environment is provided by legislation and public pressure,
both of which have significant effects on the management of a company. Government
and interest groups are stakeholders themselves, but are only included here in the aspect
of the environment. The environment is also widely cited as an important stakeholder,
either as part of the community or separately (see Appendix 1).
5.4. Employees
The fourth and final stakeholder group is employees; the second of those Berman, Wicks,
Kotha & Jones (1999) found to have a direct effect on financial performance (and one
that was also supported by Tiras, Ruf & Brown’s (1998) survey). This group is virtually
ever present in various definitions of stakeholder theory, and rightfully so. The legitimacy
of the employees’ claim comes from the fact that they have their livelihood at stake.
Employees deliver input in the form of hours and dedication and in return they receive
wages and financial security. In return for specialising their skills to fit a specific job,
employees also expect meaningful and diverse jobs as well as respect from management
and colleagues. The higher the degree of specialisation the more power an employee
possesses. By treating its employees with respect and rewarding them financially as well
and non-financially the company comes a long way in preventing employees from
exercising power in a way that may hurt the company financially (e.g. strikes, employee
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43
exodus, low productivity, absenteeism and lack of commitment). A good human resource
policy can be a competitive advantage to a corporation just as a poor one can be a
disadvantage.
5.5. Excluded stakeholders
Besides the four stakeholder groups mentioned above there are a number of other groups
of varying importance (see Figure 4 in chapter 4.1. and Appendix 1). Different
stakeholders may vary in importance from company to company, this is also true to the
above mentioned stakeholder groups. However, to form a group of stakeholders that is
generic across sectors only the most general and important can and must be included. In
this sense the groups not included lack either legitimacy, power or even both when seen
in respect to a broad sample.
After selecting which stakeholder groups to include and exclude in the analysis, a major
concern arises regarding how to judge if these stakeholders are satisfied or not
6. Stakeholder assessment criteria
As with the selection and exclusion of various stakeholder groups, the issue of
stakeholder satisfaction holds individual qualities for each company. But in order for this
study to be carried out, some criteria that can help clarify which stakeholder groups’
needs each company adequately attends to must be decided upon. Naturally, this process
is easier the more alike the companies are in regards to sector and culture, nevertheless a
relatively generic set of standards must be introduced.
When has a company done enough to satisfy the claim of a stakeholder? As mentioned,
this is difficult to determine, but perhaps it is easier to say when they have not done
enough. It is not enough to simply acknowledge the existence of various stakeholder
groups; action is required. For a company to be seen as striving to satisfy stakeholder
claims, it must signal its desire to do so and back this signal up with an investment of
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
44
either time or money. This is very similar to the investment in education focused on by
Spence (1973). Spence holds that individuals invested in education at some cost in terms
of time and money, and that this investment is a signal to potential employers of the
individuals ability to fulfill x years of education. Spence points out that this signaling
theory is applicable to other areas than just education. Morsing (in Morsing & Thyssen
eds., 2003) also emphasizes that the relevant stakeholders must be informed of a
company’s socially responsible actions, and this conclusion is directly applicable to
stakeholder theory as well.
Hence, a company can send a signal by investing in measures to satisfy the claim of one
or more stakeholder groups. This signal shows that they strive to improve their
relationship with the stakeholders (or maintain an already good relationship). So, for a
company to successfully satisfy a stakeholder group a signal is required, and this signal
must be credible in the sense that certain costs are associated with it - after all: action
speaks louder than words.
Besides broadly defining variables and setting up requirements of a financially backed
signal, it is necessary to allow for variations regarding the type of signal each company
sends. The reason for this is that different sectors may have different standards and
different companies may approach the accommodation of stakeholder claims differently.
Therefore, several options will be available for companies to be perceived as stakeholder
value maximising, and for some criteria there is not just one way of achieving fulfilment.
It is thus possible for a company to achieve no stakeholder satisfaction by not fulfilling
any of the following standards, but more importantly it is also possible to achieve a good
measure of satisfaction by fulfilling one or more criteria for each stakeholder group. This
makes for very varied degrees of stakeholder satisfaction across companies as several
criteria will be introduced. In that sense it is more varied than the division into good,
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
45
neutral and bad implemented by Tiras, Ruf & Brown (1998). These different options will
now be introduced in turn for each stakeholder group24.
6.1. Customers
Customers are interested in good products and service. This means that high quality
standards, good innovative products, timely delivery and friendly service (pre and post
sales) are among those things that customers are typically influenced by when selecting
suppliers, and also when evaluating whether they are satisfied. The most obvious signal
for a company to send is obtaining (and maintaining) a quality certificate. Such
certificates are usually ISO 9000 or ISO 900125. Other quality certificates will also be
regarded as credible signals, as they are typically expensive and time consuming to
implement and maintain. Other signals regarded as credible include product development
and finally customer satisfaction surveys (the last two also being part of the evaluation
criteria of KLD). These signals are all associated with significant costs (either in form of
manpower, money or both) which signal that companies are not ignoring customers’
claims for high quality and good service.
6.2. Shareholders
Most listed companies are well aware of the importance of treating shareholders right.
The shareholders are a powerful stakeholder group, and almost all annual accounts and
websites signal the individual company’s drive to maximise the wealth of its
shareholders. Nevertheless, not all of these signals are credible. It is not enough to simply
state the desire to maximise shareholder wealth. On the other hand shareholders cannot
expect high dividends and share price increases every year so that cannot be perceived as
a signal either. One of the major problems for shareholders is the agency problem (see
24 The criteria are based on the author’s general knowledge of various business trends and tendencies, but more importantly on a pre-survey of nine major companies perceived to have relevant interactions with the selected stakeholder groups. These companies are: Carlsberg, Coloplast, Danisco, William Demant, FLS Industries, Lundbeck, NEG Micon, Novo and Vestas. 25 Quality standards and certificates are typically associated with manufacturing companies only, but according to www.teknologisk.dk ISO 9001:2000, in particular, is also applicable to service companies etc.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
46
chapter 2.), and therefore credible signals can be measures set up to curb this problem26.
So, the actions that are the most convincing regarding the company’s desire to fulfil
shareholders’ needs are those that align the interests of management and employees with
those of the shareholders. Hence, the use of management share options/warrants as well
as employee shares are credible signals in regards to the company’s commitment to
satisfy shareholder claims. With shareholders becoming more active over time and thus
requesting more information and openness from the firm, setting up investor relation
departments is another logic way of fulfilling these shareholder needs. Whereas an
investor relations department is accepted as a credible signal, simply requesting calls
from investors is not, it is again an issue of time, manpower and money having to be
spent27.
6.3. Environment
The only non-human of the four stakeholder groups included in this survey is the
environment. The effect it has on human life and welfare is, however, enormous. This is
also why so much attention is directed at this stakeholder group. As for customers,
certificates focusing on the environment, such as ISO 14001, are the most obvious
credible signals. These certificates are achieved by performing according to certain
standards in regards to waste collection and management, disposal and recycling. As with
quality certificates it is time consuming and costly to fulfil those standards and become
certified. Another credible signal is the existence of an environmental department. Such a
department would require funds and time to improve the company’s environmental
performance. Besides those two, environmental training programs are also accepted as
credible signals. And finally, improved performance in consumption and usage that will
result in better environmental performance is also accepted. But it is again important to
emphasize that it is not sufficient for a company to announce the importance of being an
26 Corporate governance frameworks initially seem like a good measure to curb the agency problem. But companies listed on the Copenhagen stock exchange are required to reflect on the report of the 6th of December 2001 by Nørbyudvalget on corporate governance. The second part of the report is “anbefalinger for god selskabsledelse i Danmark – corporate governance i Danmark”. It is available on www.cse.dk. 27 Investors and shareholders are perceived to be the same in this thesis.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
47
environmentally friendly company, action is required. Furthermore, focusing on the fact
that one’s company is active in areas that have less impact on the environment, than is the
case for other industries, is not acceptable - improvement is virtually always possible.
6.4. Employees
For an employee to be happy and satisfied with his or her job, this particular job must be
interesting, challenging and safe. As with customers and environment, a certificate is one
credible signal. The most common certificate that focuses on employee welfare is
OHSAS 18001. Furthermore, training is of great importance. Training helps the
employee develop and makes the job more challenging and interesting. For training to
become a credible signal the company must either have its own training academy, use
external training or otherwise document that actual and specific training has taken place.
Again, it is not enough to claim focus on well educated employees, great chances to
develop further and so on, so forth. Another employee satisfaction criterion is the
proportion of employee elected board members. Most Danish companies have employee
elected board members in their board of directors28. These board members serve as
representatives for the employees as well as to provide expert knowledge on certain
company functions. As the total number of board members vary extensively from
company to company, it is not enough to merely use the number of employee elected
members as an indicator for employee satisfaction. Therefore the proportion of employee
elected members to non-employee elected ones will be calculated, and if this ratio is
higher than one third the company will be perceived as stakeholder satisfying for this
criterion29. The fourth criterion included is employee satisfaction surveys; as with
customer satisfaction surveys, considerable costs are associated herewith. The final
criterion is equal opportunity frameworks. In a modern society discrimination in the work
place (when it comes to hiring etc.) should never occur, and the companies that deal with
28 The employees in Danish companies must elect to become represented. It is, however, not all companies where representation is elected. Representation, if elected, is a minimum of two members. 29 The ratio of one third is chosen based upon the distribution among the companies investigated as well as upon personal judgement.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
48
the problem in the proper fashion are seen as being more stakeholder focused than those
that do not.
The result of the process of selecting the relevant stakeholder groups and satisfaction
measures for the companies on the Copenhagen Stock Exchange is shown visually in
Figure 7
Figure 7: Selected stakeholders and satisfaction criteria
Besides the different criteria mentioned above, data on a number of other criteria was
collected. Those other criteria were, however, not included in the survey. The reason for
not including these criteria varied. For some it was because too few companies fulfilled
the criterion. For others, different weaknesses kept them out of the final survey. The
Environment: - Environmental certificate - Environmental training -Environmental dep. - Improved usage
Employees: - Training - Employee elected board members - Employee certificate - Employee surveys
Shareholders: - Employee shares -Investor relations dep. - Management shares
Customers: - Quality certificate - Product dev. - Customer survey
Company/ Management
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
49
excluded variables included: listings of sustainable indexes, corporate governance
frameworks, green accounts and quality departments
7. Purpose, methodology and data
After establishing which stakeholder groups are to be included, and before conducting the
statistical tests, it is necessary to clarify the following: purpose of the analysis, how it is
to be conducted and the sample to provide the foundation.
7.1. Hypotheses
Many theorists (including Freeman 1984, Evan & Freeman 1988, Svendsen 1998) claim
that a successful implementation of stakeholder oriented management can lead to
improved financial performance, and that it is, in fact, superior to the traditional
shareholder value maximisation approach. Those theorists, however, neglect to
empirically prove this point. They do, as Donaldson & Preston (1995) criticised them for,
often justify the theory with purely normative arguments. Berman, Wicks, Kotha & Jones
(1999) found some support for the instrumental thesis in form of a direct link between the
relationship with employees as well as product quality/safety and financial performance.
Tiras, Ruf & Brown (1998) also found some support for the instrumental thesis in form of
a link between customers, environment and employees and financial performance. The
goal of this thesis is therefore to investigate this link. Consequently, the instrumental
hypothesis is central to this analysis.
Hypothesis I: maximising stakeholder value leads to improved financial performance.
Clearly, this hypothesis is very broadly defined. Therefore, four sub-hypotheses are
introduced. These hypotheses are based on Hypothesis I and the selected stakeholder
groups.
Hypothesis Ia: maximising customer value leads to improved performance.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
50
Hypothesis Ib: maximising investor value leads to improved performance.
Hypothesis Ic: maximising environmental performance leads to improved performance.
Hypothesis Id: maximising employee value leads to improved performance.
As mentioned above, Berman, Wicks, Kotha & Jones (1999) found some support for
Hypothesis Ia and Id, whereas Tiras, Ruf & Brown (1998) did for 1a, 1c and 1d. There is,
however, no evidence from Denmark, and one might expect a different outcome from a
2003 Danish study than from US based studies from 1998 and 1999. These expectations
are mainly based on the differences in the basic business philosophies exemplified
through the theoretical section of this thesis. Each of the four hypotheses has between
three and five sub groups, depending on the number of identified assessment criteria. The
satisfaction of these is of great relevance to the analysis, but they are not stated as formal
hypotheses.
In order to test the central hypothesis of this analysis several other questions are of
interest, concurrently as well as pre and post Hypothesis I. First and foremost, the
development of stakeholder focus in Denmark. As stakeholder theory (as well as theories
on business ethics and corporate social responsibility) has advanced and gained
popularity, it is expected that companies have become more stakeholder oriented over
time. This represents what Donaldson & Preston (1995) call the descriptive thesis, which
means that it simply helps map the popularity of stakeholder theory in Denmark.
Hypothesis II: implementation of stakeholder value maximising measures has increased
over time.
In connection with this hypothesis the relationship among the different stakeholder
groups is also interesting to investigate.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
51
Hypothesis IIa: companies that perform well with one stakeholder group perform well
with other groups.
Finally, focus on improvements in stakeholder satisfaction is also of interest. Does an
improvement in satisfaction of one or more stakeholder groups bring an improvement in
financial performance, or is the connection less visible? This question combines
hypotheses I and II in the sense that it adds dynamism to the measurement of stakeholder
and financial performance.
Hypothesis III: improvements in stakeholder satisfaction lead to improvements in
financial performance.
The hypotheses are not tested in the order they are listed. Rather, the central hypothesis,
Hypothesis I, is the most important hypothesis, and therefore the main focus of the
analysis will be on the various aspects of that in particular.
7.2. Statistical method
Testing the hypotheses set forth above is a matter that requires extensive statistical
analysis, using several different methods. The statistical results are achieved using SPSS
supplemented by some output from Microsoft Excel.
Initially, a simple descriptive analysis is carried out. The purpose of this is to map
developments in the use of the various stakeholder value maximising measures (the
independent variables). This visual analysis is based on the total stakeholder
performance, but also deals with the developments in the individual stakeholder
measures. The visual analysis is complemented by Pearson’s correlation matrix, which
tests the correlation between the individual measures. This will aid in illustrating any
significant correlations that may eventually limit the informational value of one or more
variables. The correlation coefficient measures the degree of linear relationship between
two variables (Aczel, 1996), and the coefficient shows how strongly related the variables
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
52
are (positively or negatively). There are several assumptions underlying correlation
analysis (Coakes & Steed, 1999, p. 53):
1. Related pairs – data must be collected from related pairs.
2. Scale of measurement – data should be interval or scale.
3. Normality – the values of each variable must be normally distributed.
4. Linearity – there must be a linear relationship between the two variables.
5. Homoscedasticity – a roughly constant variability in values across variables.
These assumptions are not formally tested in this thesis. Assumption three is very
important for Pearson’s correlation factors, but due to the fact that all the independent
variables are dummy variables this is difficult/impossible to test, but it is assumed that
they hold the qualities of normally distributed variables30.
Testing for differences between two groups of companies is carried out using
independent samples t-tests. This allows for testing of the differences between two
groups, but more importantly also enable the testing of the differences that follow
improvements in stakeholder satisfaction. The independent samples t-test assumes that
both groups of variables are normally distributed, but is, however, robust towards
deviations from this assumption (Nielsen & Kreiner, 2003).
The linear relationship between variables can be explained by high correlation
coefficients, but high correlations do not necessarily imply causality (Pindyck &
Rubinfeld, 1998). So when aspiring to explain any causal relationship between a
dependent variable and one, or more, independent variables linear regression analysis is
required. Simple as well as multiple regressions will be used to test the linear relationship
30 Under normal circumstances the Spearman rank correlation coefficient could be used as an alternative (or to complement), but because of the binary quality of the variables in this sample it is not possible to rank them.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
53
between independent and dependent variables. There are a number of assumptions that
has to be fulfilled for the regressions to be valid (Aczel, 1996)31.
1. Linearity – there must be a linear relationship between the variables. This
assumption cannot be formally tested, but looking at bivariate scatter plots of the
variables can help point to evident weaknesses. This method is, however,
problematic when all variables are binary. Fortunately, multiple regressions are
not affected greatly by minor deviations from this assumption; therefore, no tests
of this assumption are carried out32.
2. Non-random independent variables – the only randomness in the value of the
dependent variable should be from the residuals.
3. Normally distributed residuals – whether or not the residuals terms are normally
distributed can be visually tested by looking at scatter plots or histograms of the
standardised residuals. The errors ought to follow the normal distribution in the
histogram. Histograms are included in all the appendices for simple and multiple
regressions (e.g. Appendix 9). There is naturally some deviation from the normal
curve. This is nonetheless perceived as acceptable and the residuals are
consequently accepted as normally distributed33.
4. Homoscedasticity – if the variance of the residuals is not constant, the estimation
method of linear regression is not efficient. Heteroscedasticity can be detected by
studying residual plots, or by running a LM test. If the LM test is significant there
is a breach of the assumption of homoscedasticity and the validity of results of the
regression diminishes. Appendix 2 includes selected LM tests for this analysis.
Focus is on one year and one performance measure, but the results are supported
31 Assumptions one through four are relevant for simple as well as multiple regressions, whereas assumption five only regards multiple regression. 32 http://www.statsoftinc.com/textbook/stmulreg.html#assumptions 33 Nevertheless some outliers of the dependent variables will be removed from the original dataset to create additional datasets for analysis, see section 7.4.7.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
54
by a low number of tests on other variables, years, datasets and performance
measures34. As only one variable shows signs of heteroscedasticity, further tests
are not carried out.
5. No multicollinearity – This phenomenon implies a linear relationship between
two or more independent variables. High correlations can help identify possible
multicollinearity problems, but not always. It may very well be that
multicollinearity occurs among more than two variables, thus making it
impossible to spot using correlation matrices. Multicollinearity makes interpreting
the results of the regression difficult if the degree is high (Pindyck & Rubinfeld,
1998). The variance inflation factors (VIF) included in the multiple regressions
prints in the various appendices can assist in indicating the degree of
multicollinearity. Multicollinearity exists in this analysis, as it does for all
multiple regressions to some degree, but the degree is not worryingly high35.
The assumptions are not tested further in this thesis, but the results are included in the
relevant appendices for the reader to study additionally if this is required. Throughout the
analysis confidence intervals of 90 per cent are used36. Only the most important results
are included in the text. The reason for only including selected results is the sheer scope
of the analysis, and all other relevant results are included either in the appendices or on
the enclosed CD.
7.4. Data
Now it is clear what information is required for this analysis to be carried out. The next
section deals with how, where and when the information is obtained.
34 See Table 2 and Table 3 for variables and performance measures and section 7.4.7. for a definition of the different datasets. 35 Aczel, A. D.(1996) refers to VIF values of five or six as being of concern. As the values in these regressions are all below two, multicollinearity is not seen as a major problem. 36 For the correlation matrices levels are however pre-set by SPSS at 95 and 99 per cent, and these levels will subsequently be used.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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7.4.1. Sample
The sample that is to form basis for the empirical survey is based on the companies listed
on the Copenhagen Stock Exchange in Denmark on the 1st of August 2003. The total list
encompasses 196 companies that can be divided and subdivided in to various categories
according to the Global Industry Classification Standard (GICS®)37. The different
categories of division are: sector, industry group, industry and sub-industry. Some groups
of companies under these standards are, however, not suitable for a generalisable study of
the instrumental justification of stakeholder theory. Therefore, a number of companies
have been eliminated based on GICS® category as well as company-specific merits. The
groups eliminated are:
Financial companies & Banks
Media
Hotels, Restaurants & Entertainment companies
Specialty stores and sellers of non-industrial products
Telecommunications suppliers
Non-manufacturing IT companies, i.e. software developers
Extraordinary small companies and holding companies functioning as investment
companies.
Companies where information was not available38.
Besides those companies that are altogether eliminated from the sample quite a few
decisions has had to be made regarding which of more companies to include and
exclude. These are:
37 The GICS® for the Copenhagen stock exchange of the 4th of June 2003 is applied. The standards were developed by Standard & Poors and Morgan Stanley Capital International and were launched on the 2nd of August 1999. See www.standardandpoors.com and www.cse.dk for more information. 38 This was the case with united plantations’ three listed companies. All three are listed on the Copenhagen stock exchange, but no information is available through www.cse.dk, Account Data, the library at the Aarhus School of Business or Statsbiblioteket in Aarhus.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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Reoccurring companies. Companies listed more than once in the form of different
share types (a & b) or with different branches. These companies are obviously
only included once. When any doubt occurs regarding which company to include,
focus was yet again on production, industrial service and handling of industrial
products.
Holding companies that are closely related to other, already included, companies.
Companies that have merged during the period are assigned the stakeholder
profile of the larger of the two before merging (estimated based on income, assets
and number of employees)
This results in a sample consisting of companies from various sectors but with focus on
production, industrial services or sales & distribution of heavy industrial products. The
total number of companies has been reduced to 89 and the distribution based on sectors
can be seen from Figure 8. A list of all the companies included is found in Appendix 3. A
sample of this size is acceptable when compared to the number of independent variables
included in the analysis39.
Figure 8: Distribution of companies – based on sectors
0
5
10
15
20
2530
35
40
45
50
ConsumerDiscretionary
ConsumerStaples
Health Care Industrials InformationTechnology
Materials Utilities
7.4.2. Data collection
Following the decision to base the degree of stakeholder satisfaction for each company on
credible signals, it is crucial to determine how to find and interpret these signals. The
39 Coakes & Steed (1999) require a minimum of five times more cases than independent variables. In this situation that results in a minimum of 75 cases for 15 variables. And as 15 variables is absolutely the highest number of varibles that will be used, this level is acceptable.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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interpretation of the signals ought to hold few complications; the signals should thus be
clear and indisputable. The identification of the signals should be based on the same
media for all companies, hence achieving consistency. There are different ways for
companies to signal what they desire. The most obvious are corporate websites, annual
accounts and press releases/media interaction40. As statements to the press are used to
differing extents by Danish companies, and media coverage based information can be
very hard to collect, these options were immediately dismissed.
Whether to use corporate websites, annual accounts or possibly both was another matter.
In order to map the developments in stakeholder focus and the possible changes in
financial performance as a consequence of such measures, the main source of information
should be available not only for 2003, but for a period before that as well. This resulted in
annual accounts becoming the primary source of data. The option to complement the data
from the annual accounts for 2002 with information from the current website was,
furthermore, dismissed, as this could lead to diminished continuity of the survey. Another
reason for this dismissal was a sample study conducted for 18 of the 89 companies in the
sample (approximately 20 per cent). When comparing the information gathered from the
randomly chosen websites with that from the annual accounts there was very little, if any,
additional information available on the websites. In all cases, but one, the annual account
held more information than the website. The application of the signalling approach only
to the annual accounts can unfortunately result in too much focus on investors. The
annual accounts must first and foremost satisfy legislative rules, but besides that they are
most likely aimed at investors and market researchers. Therefore the information
included in the annual account could tend to be that, which the company believes that the
investors are interested in hearing about. But, for the signalling approach to be applied in
a consistent manner this problem must be overridden, though not ignored.
40 Data collection through questionnaires, interviews and case studies is not applicable when the signalling approach is applied; consequently these methods are not discussed further.
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7.4.3. Time frame
As discussed above, the aspect of changes in stakeholder and financial performance over
time is highly interesting. By collecting data for more than one year it becomes possible
to map the development in stakeholder focus. It also enables us to see whether there has
been a change in the relationship between stakeholder performance and financial
performance. The most obvious year to include was the last completed financial year,
namely 2002. This guaranteed that all companies had completed their annual accounts,
thus leaving no holes in the dataset for 2002. The two other years selected were 1999 and
199641.
7.4.4. Independent variables
All the independent variables are set up as binary variables based on the signalled criteria
from chapter 6. If a company does not credibly signal that it fulfils a certain variable it is
perceived as not fulfilling it, thus assigning the value zero to the variable. If there is a
credible signal the value one is given to that variable for the specific company. It is also
interesting to include summed variables, summed across stakeholder groups as well as
total stakeholder satisfaction. The independent stakeholder group variables are the sums
of all the dummy variables for that group divided by the number of variables. The result
of this is the proportion of the measures fulfilled for that group. The total sum is simply
all the dummy variables summed for each company for each year. This measure ignores
the effects of the different groups and individual measures, but provides a score for
general performance. Summing the variables may also result in some problems with
ignoring the correlations between the individual summed variables (see sections 7.2. and
8.1.).
Finally all the variables are coded to make them easier to work with and to fit the
requirements of SPSS. These codes are listed in Table 2. Each variable in this survey has
41 The reason for not going back further was that very little proof of stakeholder focus was found for 1996, hence no proof of stakeholder orientation was expected for 1993 or earlier.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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been given a three or six letter code to which is added the year in which it is valid (96, 99
and 02).
Table 2: Coding of individual variables
Group Description Code Quality certificates such as ISO 9000, 9001 and 9002 quacer
Extensive R&D, product development and improvements prodev
Customer satisfaction surveys Cussur
Customers
The fraction of customer measures fulfilled cus
Employee shares empsha
Investor relations department invrel
Management share options, warrants and shares mgmsha
Shareholders
The fraction of investor measures fulfilled inv
Environmental certification such as ISO 14001 and EMAS envcer
Environmental training of employees envtra
Environmental department envdep
Improved usage and consumption of material, energy etc. impuse
Environment
The fraction of environmental measures fulfilled env
Employee training emptra
Employee elected board members empboa
Certificate of health and safety such as OHSAS 18001 empcer
Employee satisfaction survey empsur
Equal opportunity and fair employment terms Equopp
Employees
The fraction of employee measures fulfilled emp
Total The summed total number of individual measures sum
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7.4.5. Financial data and performance measures42
In order to test the instrumental hypothesis of stakeholder theory it is crucial to select one
or more measures of financial performance. These measures should represent what the
individual companies see as a measure that reflects financial success. There are many
different measures to choose from, but the three used in this analysis are market to book
value (mb), return on assets (roa) and return on equity (roe)43. Three, rather than one,
measures are used to achieve greater validity and consistency of the tests. Table 3 specify
the individual measures, all of which are calculated using data from Account Data.
Table 3: Performance measures
Measure Code
Market value of equity / Book value of equity* mb
Earnings Before Interests and Taxes/ Book value of assets roa
Net Income / Book value of equity excl. minority interests roe
*Calculated by Account Data, adjusted for dividends and issue of new stock. For all three measures a three year average is used44. This provides the most useful
measure by removing some of the noise in the dataset. To some extent it also corresponds
to the method used by Agle, Mitchell & Sonnenfeld (1999) where they used two year
averages of roa and roe in their analysis of stakeholder attributes and salience45. The
correlation matrices in Appendix 4 show that the three performance measures are highly
correlated, especially for 2002 and 1999. Therefore, if one measure suffers from
occasional faulty information the other two should be more reliable. Consequently, in
cases where the results are not consistent, they will be based on the generally most
steadfast and trustworthy measures.
42 This part of the data collection was made in collaboration with P. Fløjgaard. 43 Initially Economic Value Added® was selected, but as it was impossible to obtain the relevant information for the required time period, EVA® was substituted with market to book value. 44 For SPSS use the financial variables 0002, 9799 or 9496 is added to their original code, e.g. roa0002. 45 In this analysis three year averages did, however, provide more consistent results than two year averages. Agle, Mitchell & Sonnenfeld (1999) also deducted an industry average to better identify top performers. Due to small groups representing several of the industries in this sample this method is, however, not applied (See Figure 8).
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
61
7.4.6. Missing data
Besides the pilot study and the study of the 18 websites mentioned in chapter 6. and
7.4.2., the actual analysis had to be conducted for 89 companies over the period of three
years (1996, 1999 and 2002). Unfortunately information was not available for some of
the companies which resulted in marginally smaller samples for 1996 and 1999. Various
reasons are at fault for the missing information. First and foremost, some companies did
not exist in previous years. But with a few companies the annual accounts for 1996 and
1999 were not obtainable. Also, in some cases Account Data could not provide the
required information. These informational shortcomings lead to the sample for 1996 of 81
and 84 for 1999, which does not seem disturbing.
7.4.7. Construction of datasets
After visually studying the relationship between the different performance measures, it
becomes clear that there are several extreme outliers in the dataset46 (Appendix 5). This is
supported by the distribution of the residuals of the coming regressions47. Such outliers
can have a great effect on statistical tests, rendering the results more or less useless.
Therefore four datasets have been constructed.
The first dataset (data1) is the full dataset described above. This contains all information,
including outliers, which can be both positive and negative. On the positive side, all
information naturally includes all relevant information. Negatively, the full dataset will
also contain information that will bias the tests (in the shape of the extreme outliers).
The second dataset (data2) has been reduced visually. This means that the performance
measure values that seemed very extreme, when looking at data1, were removed. This
46 As the independent variables are all dummy variables, the visual relationship between independent and dependent variables makes less sense than it would have if the independent variables were scaled differently. Therefore the visual study of the dataset, in regards to outliers, has been conducted based on the individual relationships between performance measures (dependent variables). The scatter plots of these relationships in Appendix 5 clearly show the pattern with many extreme outliers. 47 See the SPSS regression results in the relevant appendices and on the enclosed CD.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
62
procedure was applied for all three performance measures and for all three years, thus
moderately reducing the dataset.
The third dataset (data3) has been systematically reduced. All values for the three
performance measure that were more than three standard deviations off the mean were
removed. This procedure was repeated until all observations had values that were within
the mean plus/minus three standard deviations. As with data2 this procedure was applied
to all three performance measures and for all three years. The result is an extensively
reduced dataset with little variation. This is positive in the sense that no one outlier can
significantly affect the statistical tests. Negatively, a great deal of information has been
eliminated and some of this information may be relevant for the analysis. Also, the
sample has been greatly reduced.
The fourth and final dataset (ranked) ranks the values of the three performance measures.
This eliminates some of the noise that the outliers cause, but also the explanatory value in
absolute terms as the results are relative. What is especially attractive about the ranked
dataset is that no data is eliminated from the analysis, and it thus provides the largest
possible sample.
Various parts of the analysis are tested using all four datasets. The results of the different
datasets are compared, and the most useful ones are selected for extensive analysis. This
means that some of the tests are performed on all four datasets, whereas some are limited
to fewer datasets.
8. Results
After selecting which stakeholders are relevant, determining how they are satisfied, how
the financial implications are tested and finally which companies to use as a sample, the
matter of interpreting the results of the statistical tests is crucial.
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8.1. Descriptive statistics
First and foremost, studying the developments in focus on stakeholder satisfaction among
Danish listed companies is well worth the effort. Besides directly testing what Donaldson
& Preston (1995) refer to as the descriptive thesis, it will provide a basis for further
discussion of the financial implications. The main inclination is to view companies as
becoming increasingly focused on the needs of various stakeholders. Whether this notion
is based on improved performance, or merely caused by legislative changes and
increasingly aggressive media is not relevant when testing the descriptive hypothesis.
Looking at the average cumulative number of measures undertaken by the companies in
the sample and then studying the development from 1996 through 1999 and finally up to
2002 is fairly straightforward, but also very interesting.
Figure 9: Developments in stakeholder performance
Average number of measures per company
0
0,5
1
1,5
2
2,5
3
3,5
4
1996 1999 2002
year
num
ber
As Figure 9 above clearly shows, there has been a significant increase in the
implementation of the various stakeholder value maximising measures. The average
number of measures has more than doubled from 1996 to 2002, ending up at 3.55
measures out of 15 possible per company. This turn of events implies increased overall
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
64
stakeholder focus, but fails to explain if this is consistent across stakeholder groups and
individual measures.
Appendix 6 includes figures that show the progression for each of the 15 measures from
1996 through to 2002. This will aid in the explanation of what might drive the increase in
Figure 9, and what might hold it back. When disregarding equopp and quacer, the
remaining 13 measures show a gradual increase in the fractions of companies that
signalled fulfilling these from 1996 to 1999 and 2002. Equopp decreases slightly from
1996 to 1999, but thereafter it rises significantly in 2002. It is important to note that the
actual number of companies applying equopp is rather limited, and that the decrease from
1996 to 1999 is only one company. The total number of companies signalling having
quacer remained more or less constant (one less company adopting it in 1999 compared
to 1996 and 2002).
The increase that described the development of the remaining 13 measures is varied. The
number of companies signalling prodev more than doubled over the period, resulting in
62 companies focusing on prodev in 2002. That makes it the most frequently occurring
signal. Proddev was the only customer focused measure that showed mentionable
increases. As mentioned, quacer remained relatively constant and cussur increased, but
only to the final value of seven in 2002.
Investor value maximising measures showed a more significant increase over the period.
Most notably mgmsha and empsha increased sharply. Mgmsha went from zero signals in
1996 to 45 in 2002. The increase in empsha was not quite as striking, but nevertheless
very significant. Invrel also showed some signs of growth. These developments points to
an increase in shareholder oriented management, but that does not necessarily exclude an
increase in general stakeholder focus. This conclusion is consistent with the increased
focus on corporate governance and the protection of shareholder rights.
The measures focusing on environmental improvement have also seen some degree of
increase. The increase in envcer is the most remarkable, with total numbers increasing
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
65
from four in 1996 to 30 in 2002. Along with a rather great increase in impuse and slighter
increases in envdep and envtra this points to a greater focus on environmental issues over
recent years.
Employees is the group with the most sub-variables, nevertheless it is also the one with
the least visual improvement in the signals sent by companies within the sample. As
mentioned, equopp actually decreased slightly from 1996 to 1999, but then increased for
2002. Empboa is relatively constant over the period, which may be due to the
requirements imposed by current legislation (see section 6.4). Surprisingly, empcer only
increased slightly, as did empsur. In fact, only emptra showed a noteworthy increase over
the period. So, even if many companies describe their employees as “our most important
asset” little is actually concretely done to improve their conditions.
The general increase in “score” across companies combined with the positive
development in most individual variables points to support for Hypothesis II. Based on
the descriptive data in this section it is safe to assume that more and more stakeholder
value maximising measures are being implemented in Denmark. This is particularly true
for inv and env, but to some extend also for cus and emp.
Correlation matrices can help clarify the relationship among the individual variables. The
Pearsons correlation matrices for the individual variables for all three years are found in
Appendix 7. For 2002 many of the variables are highly correlated. Especially emptra and
envcer are significantly correlated with quite a lot of the other variables, seven and eight
respectively. The most notable patterns in the correlation matrix are rather logical. First
of all, the ownership of one of the three certificates (quacer, envcer and empcer) is highly
correlated with ownership of the other two. Second, environmentally focused firms tend
to perform well on more environmental issues, especially those who fulfil envcer. All of
the significant correlation coefficients are positive, and so are most of the non-significant
ones. This implies a positive relationship in the presence of two variables. Initially the
correlation matrix can help illustrate that there may very well be a pattern of companies
that do well with one stakeholder group also tend to do well with other groups. This
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
66
provides support for Hypothesis IIa, which states that once a company is stakeholder
focused it tends to focus on more stakeholder satisfaction criteria than just one. The
correlation matrix for the category variables (Table 4) points to the same conclusion as
the individual variables, namely that the satisfaction of one group is often accompanied
by that of another (see also Appendix 8).
Table 4: Correlation matrix for category variables
Correlations
1 ,286** ,293** ,395**,286** 1 ,136 ,307**,293** ,136 1 ,362**,395** ,307** ,362** 1
CUS02INV02ENV02EMP02
CUS02 INV02 ENV02 EMP02
Correlation is significant at the 0.01 level(2 il d)
**.
The number of significantly correlated variables is much lower for 1999 and especially
1996. Furthermore, the informational value for these years (again especially 1996) is
limited by some variables are not fulfilled by any companies at all. This makes the
calculation of correlation coefficients impossible. It thus serves to support the conclusion,
that companies are becoming more and more stakeholder focused over time and thus
Hypothesis II.
It is, however, important to remember that the discussion above only helps map the
developments in stakeholder focus and the relations between the individual stakeholder
measures. It does not imply whether or not it is financially viable, nor any other reasons
why the companies have elected to become more stakeholder focused. A final
consequence of the relatively high degree of correlation is the fact that it may make the
interpretation of the upcoming regressions somewhat more complicated.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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8.2. Simple regression
The central part of this thesis is analysing whether satisfying stakeholder criteria
improves financial performance. The most basic way of doing this is looking at the
relationship between one variable and financial performance by running a simple
regression. Table 5 sums up the unstandardised coefficients highlighting significant
simple regressions for 2002 in order to provide an overview of the tests. Appendix 9
gives an example of the output from SPSS using only data on envcer for 200248.
Table 5: Simple regressions for 2002 – all individual variables
MB ROA ROE MB ROA ROE MB ROA ROE MB ROA ROEquacer 9,581 0,051 0,124 0,828 0,042 0,088 0,362 0,040 0,065 6,776 12,943 12,070prodev 11,683 -0,010 0,082 0,501 -0,005 0,006 0,317 -0,020 -0,008 3,588 1,223 4,147cussur 29,286 0,046 0,114 0,825 0,038 0,063 0,144 0,036 0,031 -0,938 8,218 6,202empsha 29,938 0,032 0,162 2,083 0,027 -0,035 0,893 0,024 0,020 22,622 11,899 12,171invrel 0,768 0,031 0,064 0,371 0,023 0,045 0,303 0,026 0,031 4,103 8,921 5,186mgmsha 10,352 0,038 0,138 1,020 0,023 0,035 0,325 0,038 0,058 15,607 13,710 15,777envcer 12,670 0,073 0,147 0,765 0,062 0,102 0,278 0,059 0,096 12,690 19,359 16,845envtra 13,069 0,053 0,121 -0,376 0,045 0,078 0,092 0,043 0,064 0,097 15,096 10,365envdep 5,737 0,052 0,106 -0,222 0,045 0,089 0,028 0,043 0,076 -9,205 18,436 15,045impuse 12,010 0,051 0,088 0,684 0,041 0,090 0,578 0,045 0,074 9,528 17,289 13,964emptra 6,471 0,035 0,076 0,806 0,029 0,062 0,029 0,044 0,048 6,011 11,711 8,002empboa -1,980 -0,043 -0,060 -0,018 -0,047 -0,068 0,042 -0,023 -0,057 -5,145 -12,861 -10,506empcer 49,706 0,058 0,165 1,668 0,050 0,102 -0,488 0,048 0,064 10,871 11,231 12,290empsur 6,301 0,070 0,100 0,534 0,062 0,082 0,174 0,060 0,069 5,825 20,465 11,400equopp 49,771 0,020 0,044 1,847 0,012 -0,008 1,261 0,022 0,020 19,703 7,443 5,582Unstandardised coefficients, significant values highlighted.
Data 1 Data 2 Data 3 Ranked
When first focusing on data1 for 2002, it is clear that only a limited number of the 15
variables are significant and can actually be linked with improved performance. Also, it
may seem as if there is little continuity among the financial measures, as it is not the
same variables that are significant for the different performance measures. Only envcer
and empsha are significant for two of the three financial measures. The removal of
extreme outliers that leads to data2 and data3 does, however, help create a little more
order in the patterns. It is clear from Table 5 that the market-to-book values were affected
the most by the outliers. The radical change in the unstandardised coefficients and
significance levels of mb when removing outliers is one reason why more focus will be
48 As a consequence of the vast number of regressions required for this analysis the remaining simple regressions for 2002, and all those for 1996 and 1999, can be found on the enclosed CD. A total of 540 simple regressions have been run for the individual variables. This is a result of 15 variables, three performance measures, and four data sets for three years.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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directed at roa and roe from here on. Mb simply tends to be too volatile and inconsistent.
Another reason is that mb tends to have less in common with roe and roa than those two
have with one another, although the they are significantly correlated (Appendix 4).
Nonetheless, mb will be used as a supplement to roe and roa.
As Table 5 clearly shows, a great deal more variables are significant when regressed
against ranked performance values. This implies a relationship between fulfilling the
stakeholder value maximising criteria and financial performance - relative to the other
companies in the sample. Interestingly the ranking leads to a very improved fit for roa
and roe, but not so much for mb. This is quite the opposite of the result of removing
outliers from the sample, and it again points to the inconsistency of mb as dependent
variable. The ranked sample provides support for the acceptance of empsha, mgmsha,
envcer and impuse as highly related to financial performance. All four of these variables
are significant for all three performance measures. Furthermore, quacer and empboa are
significant for roa and roe.
When looking at all datasets the most noteworthy pattern is that envcer and impuse are
the two variables that most consistently seem to produce an improved financial
performance. For all four datasets unstandardised coefficients were positive for most of
the significant regressions, only empboa showed a significantly negative relationship49.
This means that increasing the relative number of employee elected board members will
actually result in diminished financial performance. The coefficients of determination
(R2) values are relatively low, especially for data150. The values do, however, improve
slightly as the outliers are eliminated and values ranked.
49 It is important to bear in mind that the unstandardised coefficients for ranked do not imply the direct effect fulfilling a measure will have on the performance of an individual performance measure. The reason for this is the previously mentioned fact that ranking the dataset results in the financial measures being relative. The unstandardised coefficient can still be used as an indicator whether the relationship is negative or positive. 50 R2 tends to overestimate whereas adjusted R2 compensate for the over optimistic R2 values by adjusting for the number of variables in the model as well as the sample size. R2 always increase when adding another variable, but adjusted R2 may fall, and even become negative (Pindyck & Rubinfeld, P. 90, 1998).
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The importance of the increase in stakeholder focus documented in section 8.1. is
strengthened further by the patterns in the simple regressions for 1996 and 1999. The
simple regressions for the two years are found on the enclosed CD, and they initially
provide very little in terms of a distinct pattern. The ranked dataset shows much the same
signs as the other three datasets for 1996 and 1999. Inconsistency characterises the results
for previous years, with only envcer being significant for both roa and roe in 1999.
Emptra is significant for roe and mb in 1999 as well, and equopp is for 1996. The lack of
consistency of significant regressions across datasets and years points to less weight in
the relationship between the individual measures and financial performance in previous
years. Hence, the increase from 1996 and 1999 to 2002 may indicate that, not only, do
more companies focus on satisfying stakeholders, but that doing so is becoming
increasingly viable - financially. As previously mentioned, missing information may also
be partly to blame for the lack of informational value of 1996 and 1999.
After testing the simple regressions for all 15 variables, the relationship between the four
stakeholder groups and financial performance will be tested. The stakeholder group
variables can clarify whether focus on the entire stakeholder groups, and not just one
individual measure, leads to improved financial performance. This approach does,
however, ignore the correlations between variables within one group. Nonetheless, it
provides a useful tool for evaluating the relationship between stakeholder and financial
performance.
Table 6 summarises the unstandardised coefficients and which groups are significant in
relation to which performance measures. Based on the conclusions from the above
sections regarding data from 1996 and 1999 the category regressions are only included
for 2002. The regression results are on the enclosed CD and an example of env is in
Appendix 10.
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70
Table 6: Simple regressions 2002 – based on categories
MB ROA ROE MB ROA ROE MB ROA ROE MB ROA ROEcus 34,482 0,500 0,244 1,681 0,045 0,106 0,843 0,045 0,056 9,666 15,583 17,424inv 32,640 0,074 0,284 2,716 0,052 0,024 1,183 0,065 0,083 33,558 25,976 26,615env 28,143 0,140 0,275 1,076 0,117 0,217 0,766 0,117 0,189 18,365 41,737 34,088emp 44,889 0,059 0,149 2,591 0,036 0,075 0,683 0,085 0,062 17,466 17,650 10,641Unstandardised coefficients, significant values highlighted
RankedData1 Data2 Data3
As with the individual variables, the regressions against the category variables result in
some noticeable differences between the results of mb and the other two performance
measures. There is a great deal of support for inv and especially env, which is consistent
with the conclusion from above where empsha, mgmsha, envcer and impuse are among
the most significant individual measures. All unstandardised coefficients are positive for
the single category regressions, which imply that the negative effects of some of the
variables are simply weighed up by the positive of the other individual variables included
in the category. R2 values remain low for the category variables, however, improving
when ranking data and removing outliers.
The results of the simple regressions on the individual variables and category variables
provide support for Hypothesis Ib and Hypothesis Ic. Most of the regressions have shown
some degree of significance for investors and environmental stakeholder value
maximisation. Although it is not all individual variables within the groups that are
significant, acceptance of these two hypotheses is clear. The other two sub-hypotheses of
Hypothesis I are only marginally significant, and they are thus rejected. This conclusion
contradicts the one reached by Berman, Wicks, Kotha & Jones (1999), who found that
customers and employees had an effect on financial performance. It also only partly
supports the findings of Tiras, Ruf & Brown (1998), namely in the aspect of the
environment. One obvious reason for the differing results is the geographical nature and
cultural aspect of the study. This analysis is Danish, whereas the other studies were US
based. Another reason is the application of the signalling approach in this study. KLD is
not limited to signalled information and may therefore include additional, and possibly
relevant, information. However, the most likely reason for the differing conclusions is the
time aspect. The fact that their studies were published in 1998 and 1999, and the analyses
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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were made prior to that date, makes the study difficult to compare with a study of 2002.
The findings of this study clearly show a continual increase in stakeholder focus, and the
link between financial and stakeholder performance is relatively weak prior to 2002.
Finally, a simple regression against the total “score” of each company is carried out. This
will provide an overview, but will of course neglect the qualities of the individual
variables and categories. It also ignores the effects of the correlations between variables
to an even greater extend than the regressions against the category variables.
Table 7: Simple regression – against summed stakeholder performance
MB ROA ROE MB ROA ROE MB ROA ROE MB ROA ROE2002 5,055 0,012 0,036 0,297 0,01 0,016 0,133 0,012 0,015 3,121 3,875 3,4331999 0,373 0,009 0,033 0,309 0,01 0,021 0,226 0,01 0,014 5,452 4,118 5,2441996 -0,741 0,01 0,012 0,321 0,01 0,022 0,031 0,01 0,013 3,841 4,747 2,812
Unstandardised coefficients, significant values highlighted
Data1 Data2 Data3 Ranked
As Table 7 shows, the financial performance of a company is highly affected by the
“total” score that the company achieves in regards to all stakeholders. Almost all
regressions are significant for all datasets, performance measures and years. The
regression results that Table 7 builds on are found on the enclosed CD. These regressions
do not provide a solution to which criteria are the most relevant, the result is merely that
the higher the “score” the better the financial performance will be. R2 values are slightly
higher than was the case with the previous regressions, but still remain low. These results
provide some support for Hypothesis I. But the weaknesses of this way of measuring
stakeholder performance does not allow for immediate confirmation of the hypothesis.
The following section will provide more strict tests of Hypothesis I
As the various criteria are costly and time consuming to fulfil, it is interesting to look at
which criteria that are the most important to focus on. This question is partly answered by
the results of the simple regressions for the individual criteria, but in order to see how
these criteria work in collaboration with each other, the relationship must be investigated
through the use of multiple regressions.
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8.3. Multiple regressions
How the interaction of more than one variable affects corporate financial performance is
central to this thesis. As the previous section documented, there is a relationship
connecting some of the individual variables and financial performance. There is also a
connection between the category variables env and inv and financial performance. It is
therefore very interesting to see if a combination of some, or all, of the individual
variables and stakeholder groups can result in superior performance.
First, multiple regressions, including all variables, are run for all years, datasets and
performance measures. To provide an overview of these regressions, R2 and significance
levels for the entire regressions are summarised in Table 8 and the regressions are found
on the enclosed CD. Furthermore, the multiple regressions for roe for 2002 for all four
datasets are in Appendix 11.
Table 8: Multiple regressions – all variables
MB ROA ROE MB ROA ROE MB ROA ROE MB ROA ROESign. 0,168 0,574 0,824 0,000 0,229 0,335 0,000 0,042 0,229 0,025 0,011 0,083R2 0,246 0,155 0,118 0,471 0,212 0,193 0,698 0,286 0,217 0,320 0,319 0,252Sign. 0,999 0,644 0,326 0,041 0,499 0,162 0,108 0,250 0,270 0,021 0,562 0,055R2 0,042 0,150 0,200 0,310 0,174 0,236 0,278 0,220 0,213 0,338 0,163 0,281Sign. 0,995 0,668 0,700 0,000 0,668 0,165 0,789 0,552 0,022 0,274 0,613 0,537R2 0,043 0,125 0,121 0,526 0,125 0,216 0,107 0,143 0,300 0,204 0,134 0,145
Significant values highlighted
1999
1996
2002
Data1 Data2 Data3 Ranked
In the multiple regressions that include all 15 variables there is a limited presence of
significant results, especially using data1. On the other hand, the regressions on ranked
for 2002 have a great deal of support. This could point towards a link between
stakeholder and financial performance relative to the other companies in the sample. The
coefficients of determination, or R2, are also high with values ranging from 25,2 per cent
for roe to approximately 32 percent for roa and mb51. This implies that 25 to 32 percent
of the variation in the performance measures is explained by the 15 variables. The ranked
51 The adjusted R2 values are lower though. These values range from 9,9 per cent (roe) over 16,3 per cent (mb) to 17,9 per cent (roa).
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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values consequently support Hypothesis I, as the set of variables in this multiple
regression work in collaboration to exemplify how stakeholder value maximisation can
lead to improved financial performance.
It is not only the overall significance levels and R2 values that are relevant to study;
looking at and understanding the individual variables qualities is also essential. Doing so
may also question the conclusion to accept Hypothesis I. In ranked, empsha, mgmsha and
envcer generally tend to have some of the highest, and constantly positive, relative
coefficients, whilst also being the most significant. This once again points to these
variables being among the most important in regards to financial performance. When
studying the results it is also important to note that several of the variables have a
negative unstandardised coefficient. This implies a negative effect of fulfilling some of
the criteria, when seen in relation to the regression of the entire set of variables.
Especially empboa has rather high negative unstandardised coefficients whilst also being
relatively significant. This implies that increasing the relative number of employee
elected board members will actually have a negative effect on financial performance.
Whereas this is consistent with previous findings, not all the negative variables were also
negative in the simple regressions. The fact that these coefficients are negative in the
multiple regressions, when it was not always so in the simple regressions, is a
consequence of the effects the individual independent variables have on one another.
One final striking thing is that the significance levels of the individual variables in the
multiple regressions change markedly when the performance variables are ranked. E.g.
mgmsha changes from being highly insignificant to being either significant or close to
significant. Other variables including envdep, impuse and prodev also vary greatly. The
variations are furthermore not consistent, some improve and some worsen. There is also
some variation in individual variable significance levels when eliminating outliers from
data1 resulting in data2 and data3, but it is most apparent for ranked. This once again
implies that the relative performance investigated in ranked is quite different from the
absolute relationship.
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74
To support the results of the multiple regressions that include all 15 variables, another set
of multiple regressions are run using the four category variables (cus, inv, env, emp). The
results of these multiple regressions are included in Table 9, and the data for roe in 2002
is in Appendix 12 with all the regressions for all three years found on the CD.
Table 9: Multiple regressions – category variables
MB ROA ROE MB ROA ROE MB ROA ROE MB ROA ROESign. 0,144 0,061 0,103 0,000 0,030 0,068 0,000 0,001 0,009 0,001 0,000 0,001R2 0,085 0,101 0,087 0,299 0,119 0,099 0,310 0,202 0,151 0,213 0,237 0,199Sign. 0,690 0,135 0,018 0,000 0,094 0,008 0,001 0,017 0,054 0,000 0,079 0,007R2 0,021 0,070 0,124 0,229 0,081 0,142 0,200 0,128 0,096 0,255 0,085 0,147Sign. 0,953 0,252 0,654 0,000 0,252 0,021 0,387 0,142 0,037 0,208 0,119 0,361R2 0,011 0,077 0,036 0,292 0,077 0,158 0,068 0,098 0,143 0,091 0,104 0,036
Significant values highlighted
Data1 Data2 Data3 Ranked
2002
1999
1996
It is obvious that the regressions for stakeholder groups are generally more significant
than the multiple regressions for all the individual variables. The results are significant,
particularly when testing the ranked dataset and those where the extreme outliers have
been eliminated. The coefficients of determination are also relatively high, with values
for ranked lying around, and even above, 20 per cent. On the other hand, some of the
unstandardised coefficients are negative for some performance measures. Especially emp,
but also cus, tend to have a negative impact on the regressions52. This means that
performing well with these stakeholder groups, when seen in relation to all four groups,
will actually have a negative impact on financial performance. This corresponds
somewhat to the results of the multiple regressions for all variables where empboa, but
also other variables from these two groups, are negative.
The fact that inv and env are significant and have the highest unstandardised coefficients,
and that these are positive, corresponds well with the findings from the simple
regressions that those two groups tend to have a more significant relation to financial
performance than the other two groups (see Table 6). This is also backed up by the fact
that empsha, mgmsha, envcer and impuse are among the most significant single variables 52 There are a few deviations from this, but generally these two stakeholder groups are prevailing as negative.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
75
(Table 5), and are among the best performers in the multiple regression of all 15
variables. Hence, the results of these regressions support Hypotheses Ib and Ic, as they
point to inv and env as indicators of improved financial performance when regressed
alongside cus and emp. It is important to bear in mind that the validity may be affected by
correlation among the underlying variables. Nevertheless, the results from the
regressions, simple as well as multiple, all point to focus on env and inv. This fact, yet
again, serves to support Hypotheses Ib and Ic, while rejecting Ia and Id.
8.3.1. Final combination of variables
In striving to improve the multiple regressions, some variables have to be removed from
the model. This is of particular importance when striving to find a set of variables
applicable to data1. None of the multiple regressions for all variables, and only very few
for the stakeholder groups, were significant when applied to the initial dataset. This
results in the informational value of the multiple regressions being very limited or even
non-existent.
The attempt to find a set of variables that can result in improved financial performance
for the entire sample thus leads to the systematic elimination of variables. The
elimination will be based on the findings from the simple and multiple regressions carried
out so far. This means that focus will be on trying to build a model around envcer, as this
have been the most successful variable. Other variables will be included and eliminated
through investigations of the following criteria:
Individual variable’s significance levels
Unstandardised coefficients – absolute values and consistency across data sets
and performance measures
Variation in data for the individual variables – how many companies have
been successful in fulfilling the individual criteria?
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The criteria are investigated for all variables, and a subjective decision is consequently
made for each of these. They will mainly be applied to ranked as this has successfully
removed a great deal of the noise found in data1. As this noise has resulted in none of the
individual coefficients being significant in the multiple regression for data1, selection
will be based on ranked and hereafter applied to data1. Data2 and data3 are suspected to
remove not only noise, but also relevant information, and the analysis will subsequently
be limited to data1 and ranked. Furthermore, this part of the analysis is only based on roe
and roa as mb tends to be very inconsistent. The mb values are included in Appendix 13
along with all the other values.
Applying the selection criteria to the datasets, the non ranked regressions only become
significant after eliminating several variables. Table 10 starts with the first model that
becomes significant for either of the performance measures. Next, one or more variables
are eliminated so it becomes possible to compare models.
Table 10: Multiple regressions, 2002 – final selection, Data1
ROA ROE ROA ROE ROA ROE ROA ROE ROA ROEBeta 0,006 0,010Sig. 0,868 0,930Beta 0,014 0,120 0,015 0,121 0,022 0,128 0,002 0,127 0,028 0,155Sig. 0,655 0,201 0,635 0,191 0,475 0,156 0,493 0,158 0,321 0,070Beta 0,022 0,078 0,023 0,046 0,019 0,075 0,017 0,072Sig. 0,442 0,365 0,424 0,353 0,508 0,372 0,550 0,388Beta 0,053 0,105 0,055 0,109 0,066 0,120 0,067 0,122 0,070 0,136Sig. 0,109 0,280 0,069 0,224 0,022 0,155 0,020 0,147 0,012 0,097Beta 0,033 0,033 0,033 0,033Sig. 0,280 0,714 0,277 0,713Beta -0,045 -0,067 -0,045 -0,067 -0,043 -0,065 -0,042 -0,062Sig. 0,146 0,459 0,143 0,455 0,160 0,465 0,167 0,488Const. 0,003 -0,072 0,003 -0,072 0,009 -0,065 -0,001 -0,080 0,015 -0,042R-sq 0,122 0,087 0,122 0,087 0,109 0,086 0,088 0,008 0,104 0,077Sig. 0,090 0,263 0,052 0,173 0,044 0,107 0,049 0,068 0,024 0,077
Significant values highlighted - for tota l regression only
Eliminated
em pboa Eliminated
em psha
Model 5
Eliminated
Eliminated
Eliminated
Eliminated Eliminated Eliminated
Total
m gm sha
envcer
im puse
quacer
Eliminated
Model 1 Model 2 Model 3 Model 4
Model 1 is significant for roa, but as the regression against roe is still quite insignificant,
more variables are eliminated. It is not until the regressions are reduced to model 4 and
model 5 that roe becomes significant, which in both cases result in only three individual
variables being included. Basing the choice of model on these results is somewhat
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
77
difficult. First of all, maintaining mgmsha instead of empboa results in a slightly better
performance for roe, whereas empboa makes the regression perform better against roa.
This dilemma, combined with the near significant result of model 3, leads to a stalemate.
Model 3 is, thus, accepted, as it includes both variables while being significant for roa
and very close for roe. The regression for model 3 is found in Appendix 13, and all five
models are included on the enclosed CD. The following four variable model is thus
accepted:
roa = 0,009 + 0,022*empsha + 0,019*mgmsha + 0,066*envcer – 0,043*empboa
roe = -0,065 + 0,128*empsha + 0,075*mgmsha + 0,120*envcer – 0,065*empboa
These two formulae are of importance when interpreting results for the entire sample of
companies. This means that they represent the best possible estimate for a model that is
significant when all outliers are included in the sample. This result can be applied directly
to calculate the effect of the four variables on roa and roe. For both regressions empsha
and envcer have the greatest positive effect on the final value, but mgmsha also have a
positive effect. On the other hand empboa has a negative effect on the value of both roa
and roe. The fact that the absolute values are greater in the regression on roe is due to a
negative constant. As the signs of the variables are consistent this does not entail a
problem. The differences in the absolute values do not have an effect on the validity of
the model and may very well be consistent with the high correlations between roa and
roe.
With regards to the central hypothesis in this analysis the regression above provides
mixed results. Hypothesis I states that fulfilling stakeholder needs will lead to improved
financial performance. This is partly supported by Model 3 as a combination of four
variables has a positive effect on financial performance. This means that if a company
fulfils these, the company as well as the stakeholders will benefit. On the other hand the
knowledge of the negative relationship between empboa and financial performance is
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
78
only beneficial to the company53. But to some extent Hypothesis I is fulfilled, dealing
properly with (some) stakeholders can improve financial performance.
Consistent with previous findings of this analysis, there is much less support for the
instrumental thesis of stakeholder theory when analysing 1996 and 1999. When applying
model 3 to the datasets of 1996 and 1999 the results are highly insignificant. This implies
that there was no relationship between stakeholder performance and financial
performance in previous years54. The results of model 3 for 1996 and 1999 can be found
on the enclosed CD. The results for previous years are also of much less interest when the
aim is to determine a set of standards applicable now. Corporations are naturally looking
for ways to improve now and in the future, not what could have helped three or six years
ago.
8.4. Compare means
The final part of this analysis focuses on the companies that have improved their
stakeholder performance over the period. In a sense, this section combines the
conclusions that stakeholder focus has increased over the years, and that doing so has
become ever more financially feasible. The companies of interest here are those that have
started fulfilling one or more criteria they did not fulfil in the previous measured year. An
example of this could be a company that acquires an environmental certificate in the
years between 1999 and 2002. These tests thus ignore the companies that perform well
from the outset, and only focus on non-performers that improve. The financial
performance of the companies that improve satisfaction of the stakeholders is compared
to that of those that do not. This should help determine if improving stakeholder
performance pays off, or if the positive effects of the regressions are mainly caused by a
group of constant performers. However, one must bear in mind that for some variables 53 Assuming that a greater fraction of employee elected board members actually benefits the employees, this information does not help the employees as it will quite likely result in a lower fraction. 54 It is important to note that model 3 is based on 2002, and that it therefore may not be the best model for 1996 and 1999. Nevertheless, as the results are very insignificant, and due to the lack of support for the stakeholder model in general for previous years, it is not deemed necessary to formulate a model for 1996 and 1999 respectively.
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the absolute number of companies that improve is low, thus limiting the statistical
validity. This is naturally due to the fact that all the companies that have already fulfilled
a criterion are not relevant to this part of the analysis, thus making the total sample
smaller55. As the number of stakeholder focused companies was very low in 1996, the t-
tests are limited to the difference between 1999 and 200256. Table 11 sums up the main
findings of the independent sample t-tests found on the CD. And yet again an example
using envcer is in Appendix 14. From the experience of previous sections focus will be
on data1 and ranked as well as on roa and roe.
Table 11: Independent sample t-test, 1999 - 2002
R O A R O E R O A R O ES ig n. 0 ,152 0 ,168 0 ,112 0 ,136M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,331 0 ,359 0 ,267 0 ,131M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,671 0 ,658 0 ,800 0 ,991M ean d iff pos itive po s itive pos itive nega tiveS ig n. 0 ,507 0 ,041 0 ,133 0 ,034M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,648 0 ,638 0 ,483 0 ,457M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,554 0 ,190 0 ,033 0 ,009M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,021 0 ,078 0 ,000 0 ,000M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,210 0 ,334 0 ,072 0 ,196M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,375 0 ,551 0 ,033 0 ,223M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,116 0 ,436 0 ,004 0 ,049M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,493 0 ,745 0 ,152 0 ,324M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,909 0 ,840 0 ,272 0 ,579M ean d iff neg a tive po s itive ne ga tive nega tiveS ig n. 0 ,336 0 ,365 0 ,367 0 ,343M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,153 0 ,490 0 ,041 0 ,094M ean d iff pos itive po s itive pos itive p os itiveS ig n. 0 ,834 0 ,856 0 ,727 0 ,822M ean d iff pos itive po s itive pos itive p os itive
S ign ifican t va lues h igh ligh te dM e an d iff: th e com pa n ie s tha t have im pro ved , i.e . a ch ieved 1 in s tead o f 0
D ata1 R anked
q uacer
p ro d ev
cussur
em p sha
invre l
m g m sha
envcer
envtra
em p cer
em p sur
eq uo p p
envd e p
im p use
em p tra
em p b o a
55 The test is only concerned with improvements of stakeholder performance. Therefore, companies that have diminished their focus on one or more stakeholder groups are eliminated from the sample along with those who maintain their level. It is expected that very few companies worsen their stakeholder performance, although it may occur with quacer and empboa as these see no, or very little, increase (see Appendix 6). 56 For some variables the number of companies fulfilling them were very low, in some cases even zero. This would render the results of the t-tests more or less useless, as there would be no difference between these and the simple regressions already made. For envdep this is also the case for 1999.
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The results of improving stakeholder performance are much the same as those found in
the simple relationship between the individual variable and financial performance. For
ranked, envcer, impuse and mgmsha are significant for both roa and roe, while empsur
surprisingly holds the same qualities. It is, however, only envcer that is significant for
both roa and roe in data1, again pointing to this variable as the most consistent cause of
improved financial performance. Empsha also find some support, and most note-worthily
this support is also visible in data1. All the significant t-tests are related with a positive
difference in mean. This means that companies that e.g. acquired an environmental
certificate between 1999 and 2002 could present significantly greater results for roa and
roe compared to those that did not acquire the certificate. There are only a few of the
results that represent a negative difference in means between the two groups of
companies, and none of these are significant. As expected, based on previous results,
empboa is the most consistent negative performer.
This approach to testing the effects of improvements in stakeholder performance on
financial performance brings a more dynamic aspect to the analysis than the previous
regressions did. It is thus possible to test the effects of change in stakeholder performance
over time, whereas the regressions were limited to testing the effects for one year at a
time. This will support the notion that the superior financial performance of the
companies that do well with stakeholders is, in fact, caused by their achievements with
stakeholders. These results might also serve as an indicator for companies striving to
fulfil one or more of the 15 measures. The measures such as empsur that find some
support here, but not in the regressions, may do so because they do not have enough
“weight” to swing the regression results yet. As a consequence, the results of the t-tests in
this regards are not as strong as those of the regressions, but they may point to future
developments. One must, nevertheless, bear in mind the statistical weaknesses caused by
the low variation of some of the variables.
So, as it was with Hypothesis I, there is some support for Hypothesis III. It is not all the
measures that will bring financial gain when improved, but there is certainly evidence
pointing out the importance of dealing properly with some stakeholder groups and more
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specific criteria. The results are still inconsistent with those of Berman, Wicks, Kotha &
Jones (1999) as there is very little support for improving performance with the employees
and no support for improving customer performance. They are a bit more in line with the
conclusions of Tiras, Ruf & Brown (1998) in the sense that there is definite support for
both envcer and impuse.
The conclusions of all the statistical tests performed in the above sections have left some
questions unanswered in regards to validity. The tests have also left some issues
unanswered and opened up new questions. The following section will therefore briefly
deal with the shortcomings of this thesis and come up with suggestions for future
research before concluding on the entire thesis.
IV. Concluding remarks
9. Shortcomings
A study of this scope will surely have some weaknesses, and that is not different for this
thesis. The most obvious shortcoming is the uncertainty whether the independent
variables that help explain the dependent variables, or if the effect actually comes from a
reverse relationship. As briefly discussed in section 3.3 it could be companies that do
well financially that improve their corporate social performance and not vice versa. The
risk of this is not quite as great for stakeholder theory as for CSR as this is focused on
actual strategy and not only ethics, but it nevertheless persists. It is not something that is
easily adjusted for, or tested, but merely a risk which the critical reader must be aware of.
The signalling approach applied in this analysis facilitated the data collection despite of
the great number of companies that were to be analysed. This approach also made the
time aspect of the thesis possible and improved continuity, but it naturally also limited the
depth of the analysis. As the annual accounts were selected as the only source of
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
82
information, the companies in effect control the information being used. This is perfectly
acceptable when applying the signalling approach, but there is always the risk of some
companies exaggerating their performance in regards to one or more stakeholder groups.
In connection with the various certificates and possibly management/employee shares it
is difficult to make a signal pass as credible if it is not, but some of the other variables
requires some flexibility in order to be used. This may unfortunately allow companies to
use stakeholder signals simply as a public relations tool without actually implementing
the required measures.
Besides the possible problems with allowing some flexibility concerning the individual
measures, the independent variables of the sample also have a few other weaknesses.
First of all, in hindsight some of the variables may have been ill chosen for different
reasons. E.g. equopp may be more relevant to studies of CSR and less so to stakeholder
theory studies. Also, only very few companies signalled having such frameworks in
place, thus reducing the usefulness of the variable. Next, prodev is difficult to measure:
when has a company invested enough, and how does it signal it? Additionally, a company
that e.g. spent vast amounts on product development and R&D in 2000 may not need
investments of the same scale again in the coming years, it may merely be enough to
adjust and improve the current product or service, possibly at a low cost. Another
problem with this variable is that almost every company in 2002 signalled focus on
prodev. Some of the other variables suffer from similar weaknesses, to varying extend.
The problem with too few or too many companies fulfilling a single criteria results in too
little variation. Problems with little variation are especially severe for the independent
sample t-tests where the companies that fulfilled the criteria in 1999 were eliminated.
This left less companies in the sample and, therefore make it even more vulnerable to the
effects of the variation. The low degree of variation questions the validity of the statistical
tests performed.
Statistically, the problem of little variation is not the only one. The fact that all the
independent variables are binary resulted in limited formal assumption tests being carried
out. The assumption that the variables are normally distributed does not seem
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
83
unreasonable, but in case of breaches of this assumption the validity of the results may be
questioned. But as this is not tested, the potential statistical problems are not dealt with.
Other assumptions for the various statistical methods used are only tested sporadically.
So with the LM tests and VIF factors implying that there are no problems with
multicollinearity, this potential problem is assumed non-existent and such assumptions
may again question the validity of the tests. In spite of these shortcomings the analysis
serves as a good indicator for trends in stakeholder theory in Denmark.
10. Suggestions for future research
As the central hypothesis was neither fully proved nor disproved, further research of the
instrumental thesis of stakeholder theory in Denmark is required. By learning from the
results and shortcomings of this analysis, problematic and time consuming actions could
be avoided or improved for other researchers. First of all, the time span would seem
excessive if the goal is to test only the instrumental thesis. And if the descriptive thesis is
of interest maybe shorter time period could be researched more thoroughly, e.g. using all
years in the period from 1999 to 2003. This could point to more recent trends, whilst
bearing in mind that over the period from 1996 to 1999 and 2002 focus on stakeholders
seemed to increase significantly.
Scrutiny of the used variables and testing of new ones could also be of interest. A number
of the variables tested in this analysis did not have any effects on financial performance;
furthermore some were eliminated prior to the statistical tests. Other variables dealing
with the same stakeholder groups could help prove/disprove the validity of the
instrumental thesis. In addition, investigating the relationship between financial
performance and some of the stakeholder groups excluded in this analysis (e.g. suppliers)
could be interesting.
Finally, collecting the information differently could help test the signalling approach
applied herein. The problems with the signalling approach are obvious (see chapter 9.),
but it is quite likely that they are not so great that they will cause problems when testing
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
84
stakeholder theory. Simply testing the signalling approach, by investigating whether the
companies fulfil what they signal, could settle this dilemma. Collecting data differently
(e.g. case studies) could also help curb the potential problem with the signalling approach
as well as the emphasis on shareholders that the annual accounts may have. Ultimately,
more research will help create a body of Danish based results to help further prove or
disprove the instrumental hypothesis of stakeholder theory in Denmark.
11. Conclusion
The emerging criticism of shareholder capitalism in its purest form has traditionally been
based on notions of ethics and morality. The position of the shareholder capitalists is
typically that the sole responsibility of a corporation is to generate profit for its owners.
This has been met with calls for socially responsible behaviour by the corporations, thus
attempting to merge traditional ethical theory with corporate management. This means
that corporations should strive to maximise profits, but under some set of limitations
dictated by their surroundings. This is seen as a trade-off, in the sense that profits are
typically thought to be higher if there are no limitations. By focusing on the relationships
between the parties that can affect, or are affected by the achievement of corporate goals,
stakeholder theory attempts to present an actual management strategy that includes other
stakeholders than just the owners.
By having management focus on developing and maintaining good relationships with
several stakeholders, the objective of the company becomes more complex. With
management devoting time and money to fulfilling the needs of several stakeholder
groups, the shareholders may have reason for concern. This concern is based on the
notion that they will be the ones to pay for the improvements of the other stakeholders,
which will lead to an agency problem. But if this new constellation results in improved
financial performance the instrumental thesis of stakeholder theory is fulfilled. The
instrumental thesis links stakeholder and financial performance, thus rendering the
concerns of the owners unnecessary. Freeman (1984) ultimately believed this link to be
true, but very few researchers have managed, or even tried, to prove the instrumental
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
85
thesis. The body of literature on the subject mainly leans on normative arguments when
justifying stakeholder theory. These normative arguments correspond to those used to
justify socially responsible and ethical behaviour, and are typically along the lines of
what companies “ought to do”. As a consequence of this lack of empirically valid
arguments this thesis strives to prove the instrumental thesis.
With emphasis on the instrumental thesis, four stakeholder groups are selected. These
groups are selected based on whether or not they have a legitimate claim on the company
and the power to enforce that claim. The four groups considered the most relevant are:
customers, investors, environment and employees. Each stakeholder group are assigned
between three and five sub-variables to help determine if the individual companies have
done enough to satisfy them. All the variables are constructed so that it will require a
credible signal on behalf of the company to be perceived as fulfilling a criterion. For a
signal to be credible certain costs, in form of time and/or money, have to be associated
with the signal. The various measures are subsequently applied to a sample of 89
companies listed on Copenhagen Stock Exchange to test stakeholder theory and financial
performance in Denmark.
The implementation of stakeholder value maximising measures in Denmark has increased
significantly over the period from 1996 to 1999 and 2002. The accumulative number of
measures implemented grew significantly, as did most of the individual measures. This
implies that the use of stakeholder value maximising measures has become increasingly
popular in Denmark.
When attempting to link the obvious increase in popularity with financial performance,
market-to-book ratio, return on assets and return on equity is used as financial measures.
The simple regressions linking the four stakeholder groups as well as the individual
variables with financial performance mainly points to significant relationships for
shareholders and environment. To get the best results the regressions were run against the
ranked values of the performance measures. This implies that performing well with
shareholders and the environment leads to improved financial performance, relative to the
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
86
other companies in the sample. Companies that have employee share plans, management
options plans, environmental certificates and improved environmental performance are
among the best performers. Fulfilling these four variables results in significantly positive
effects on financial performance. The coefficients of determination are, however,
relatively low, thus implying that the variables only explain a low degree of the total
variation in the dependent variables.
The tendencies that became obvious with the simple regressions reflected on the results
of the multiple regressions as well. Focus on shareholders and environment remains
obvious, while combining all variables found very little support. A combination of the
following variables is consequently accepted as the final model: employee shares,
management shares, environmental certificates and the fraction of employee elected
board members. The fraction of the board members turned out to have a negative effect
on financial performance, whereas the remaining variables have positive effects.
So, there is some support for the instrumental hypothesis of stakeholder theory, but not
quite enough to fully prove or disprove it. Therefore, to some extend it is still necessary
to turn to normative arguments in order to justify the instrumental thesis. More
comparable and complementary research is still required if stakeholder theory is to
become statistically valid or invalid, in Denmark as well as internationally.
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
87
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List of appendices
Appendix 1 Overview of literature – definitions of stakeholders
Appendix 2 Selected LM tests
Appendix 3 List of companies
Appendix 4 Pearson’s correlation matrix for performance measures
Appendix 5 Scatter plots for performance measures
Appendix 6 Developments for all 15 individual measures – 1996 to 2002
Appendix 7 Pearson’s correlation matrix for independent variables
Appendix 8 Pearson’s correlation matrix for category variables
Appendix 9 Example of simple regression for envcer in 2002
Appendix 10 Example of simple regression for env in 2002
Appendix 11 Example of multiple regressions for all variables in 2002
Appendix 12 Example of multiple regressions for categories in 2002
Appendix 13 Final model for multiple regressions for 2002
Appendix 14 Example of independent sample t-test for envcer for 1999-2002
Thomas Pedersen: Stakeholder Theory – lessons from Denmark
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List of figures
Figure 1: Structure of the thesis .......................................................................................... 3
Figure 2: Production view of a company.......................................................................... 18
Figure 3: Managerial view of a company ......................................................................... 19
Figure 4: Stakeholder view of a company ........................................................................ 20
Figure 5: Uses of stakeholder theory ................................................................................ 24
Figure 6: Definitions of stakeholders................................................................................ 32
Figure 7: Selected stakeholders and satisfaction criteria .................................................. 48
Figure 8: Distribution of companies – based on sectors ................................................... 56
Figure 9: Developments in stakeholder performance ....................................................... 63
List of tables
Table 1: Stakeholder classes ............................................................................................. 35
Table 2: Coding of individual variables............................................................................ 59
Table 3: Performance measures ........................................................................................ 60
Table 4: Correlation matrix for category variables........................................................... 66
Table 5: Simple regressions for 2002 – all individual variables....................................... 67
Table 6: Simple regressions 2002 – based on categories.................................................. 70
Table 7: Simple regression – against summed stakeholder performance ......................... 71
Table 8: Multiple regressions – all variables .................................................................... 72
Table 9: Multiple regressions – category variables .......................................................... 74
Table 10: Multiple regressions, 2002 – final selection, Data1 ......................................... 76
Table 11: Independent sample t-test, 1999 - 2002............................................................ 79
Appendix 1: Overview of literature
Author Purpose Method Result Definition of stakeholder.
Who are stakeholders?
Freeman (1984)
Define and describe the emergence of stakeholder theory.
Theoretical. Normative.
A stakeholder theory applicable for managers.
A stakeholder in an organisation is any group or individual who can affect or is affected by the achievement of the organisation’s objectives.
Governments, local community organisations, owners, consumer advocates, customers, competitors, media, employees, special interest groups, environmentalists, suppliers.
Evan & Freeman (1988 reprint)
Build a theory that balances the rights of the claimants on the corporation with the consequences of the corporate form.
Theoretical. Normative.
Stakeholders are groups and individuals who benefit from or are harmed by, and whose rights are violated or respected by, corporate actions.
Owners, management, local community (incl. environment), customers, employees, suppliers. (Narrow definition of stakeholders).
Donaldson & Preston (1995)
Compare evidence and concepts previously set forth by other researchers of stakeholder theory.
Finds three different aspects of stakeholder theory: descriptive, instrumental and normative. Only supports the normative justification of stakeholder theory.
Stakeholders are persons or groups with legitimate interests in procedural and/or substantive aspects of corporate activity.
Clarkson (1995)
To develop a stakeholder framework and methodology grounded in the reality of corporate social performance.
Empirical. The economic and social purpose of the corporation is to create and distribute increased wealth to all its primary stakeholders without favouring one at the expense of the others.
Primary: shareholders, investors, employees, customers, suppliers and the public stakeholder group. Secondary: further includes media and SIGs.
Freeman & Werhane eds. (1997)
To create an overview of business ethics.
Theoretical. Normative.
Contributions of more than 300 writers on all subjects related to business ethics.
Freeman (1984) Owners, financial community, activist groups, customers, customer advocate groups, unions, employees, trade associations, competitors, suppliers, government, political groups.
Mitchell, Agle & Wood. (1997)
Define who and what really counts – that is which stakeholders management should pay attention to.
Theoretical. Normative.
Use attributes (power, legitimacy and urgency) to distinguish salient from non-salient stakeholders.
Freeman (1984) et. al.
Svendsen (1998)
Theoretical. Freeman (1984) Customers, suppliers, employees, communities (including environment).
Tiras, Ruf & Brown (1998)
Testing if satisfying key stakeholders is value relevant
Empirical Found some support that customers, employees and environment has an effect on a company’s valuation coefficient and earnings.
Freeman (1984) Customers, employees, environment, community.
Agle, Mitchell & Sonnenfeld (1999)
Testing of the stakeholder salience model presented by Mitchell, Agle & Wood (1997)
Empirical. Found that the connection between attributes and stakeholder salience is significant.
Shareholders, employees, customers, government and communities.
Berman, Wicks, Kotha & Jones (1999)
Testing the model presented by Donaldson & Preston (1995).
Empirical. Found some support for the instrumental thesis as opposed to what Donaldson & Preston held.
Freeman (1984) Employees, natural environment, workplace diversity, customers and product safety, community relations.
Tirole (2001)
Discusses corporate governance in relation to stakeholder theory
Theoretical. Corporate governance is the design of institutions that induce or force management to internalize the welfare of stakeholders.
Employees, customers, suppliers, communities, potential pollutees, etc. (p.3)
Winn (2001)
Analysing complex corporate strategic decisions that involve multiple stakeholders with divergent views
Case study. Creates a framework that allows the comparison of different companies regarding organisational decisions involving divergent stakeholders.
Employees, customers, shareholders, communities, environment, suppliers, public interest groups, media, regulators.
Appendix 2 The LM tests for heteroscedasticity are conducted for all 15 individual variables against roe for 2002. in addition to that quacer is also tested for the remaining performance measures, years and finally datasets. The multiple regressions are limited to data1 and roe, roa and mb for 2002, supplemented by tests for roe for 1999 and 1996. Simple: Data 1:
:
Fixed Factors ,0103 ,9167 1 0,3383
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), quacer02b.
Standardized residuals are usedc.
:
Fixed Factors ,0087 ,7743 1 0,3789
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roa0002a.
Predictors: (Constant), quacer02b.
Standardized residuals are usedc.
:
Fixed Factors ,0089 ,7209 1 0,3958
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: mb0002a.
Predictors: (Constant), quacer02b.
Standardized residuals are usedc.
:
Fixed Factors ,0004 ,032 1 0,858
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe9799a.
Predictors: (Constant), quacer99b.
Standardized residuals are usedc.
:
Fixed Factors ,0013 ,0923 1 0,7613
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe9496a.
Predictors: (Constant), quacer96b.
Standardized residuals are usedc.
:
Fixed Factors ,0005 ,0445 1 0,8329
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), prodev02b.
Standardized residuals are usedc.
:
Fixed Factors ,0027 ,2403 1 0,624
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), cussur02b.
Standardized residuals are usedc.
:
Fixed Factors ,0038 ,3382 1 0,5609
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), empsha02b.
Standardized residuals are usedc.
:
Fixed Factors ,0078 ,6942 1 0,4047
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), invrel02b.
Standardized residuals are usedc.
:
Fixed Factors ,0356 3,1684 1 0,0751
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), mgmsha02b.
Standardized residuals are usedc.
:
Fixed Factors ,0207 1,8423 1 0,1747
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), envcer02b.
Standardized residuals are usedc.
:
Fixed Factors ,0056 ,4984 1 0,4802
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), envtra02b.
Standardized residuals are usedc.
:
Fixed Factors ,0036 ,3204 1 0,5714
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), envdep02b.
Standardized residuals are usedc.
:
Fixed Factors ,0081 ,7209 1 0,3958
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), impuse02b.
Standardized residuals are usedc.
:
Fixed Factors ,0197 1,7533 1 0,1855
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), emptra02b.
Standardized residuals are usedc.
:
Fixed Factors ,0095 ,8455 1 0,3578
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), empboa02b.
Standardized residuals are usedc.
:
Fixed Factors ,0018 ,1602 1 0,689
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), empcer02b.
Standardized residuals are usedc.
:
Fixed Factors ,0058 ,5162 1 0,4725
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), empsur02b.
Standardized residuals are usedc.
:
Fixed Factors ,0019 ,1691 1 0,6809
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), equopp02b.
Standardized residuals are usedc.
Data 2:
:
Fixed Factors ,0133 1,1704 1 0,2793
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), quacer02b.
Standardized residuals are usedc.
Data 3:
:
Fixed Factors ,0061 ,5246 1 0,4689
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), quacer02b.
Standardized residuals are usedc.
Ranked:
:
Fixed Factors ,014 1,246 1 0,2643
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: rroe0002a.
Predictors: (Constant), quacer02b.
Standardized residuals are usedc.
Multiple: Data 1 (only):
:
Fixed Factors ,1145 10,1905 15 0,8076
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe0002a.
Predictors: (Constant), quacer02, prodev02, cussur02, empsha02,invrel02, mgmsha02, envcer02, envtra02, envdep02, impuse02,emptra02, empboa02, empcer02, empsur02, equopp02
b.
Standardized residuals are usedc.
:
Fixed Factors ,0806 7,1734 15 0,9527
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roa0002a.
Predictors: (Constant), quacer02, prodev02, cussur02, empsha02,invrel02, envcer02, mgmsha02, envtra02, envdep02, impuse02,emptra02, empboa02, empcer02, empsur02, equopp02
b.
Standardized residuals are usedc.
:
Fixed Factors ,1961 15,8841 15 0,3898
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: mb0002a.
Predictors: (Constant), quacer02, prodev02, cussur02, empsha02,invrel02, mgmsha02, envcer02, envtra02, envdep02, impuse02,emptra02, empboa02, empcer02, empsur02, equopp02
b.
Standardized residuals are usedc.
:
Fixed Factors ,0611 4,888 15 0,993
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe9799a.
Predictors: (Constant), quacer99, prodev99, cussur99, empsha99,invrel99, mgmsha99, envcer99, envtra99, envdep99, impuse99,emptra99, empboa99, empcer99, empsur99, equopp99
b.
Standardized residuals are usedc.
:
Fixed Factors ,0544 3,8624 15 0,9982
Model R^2 nR^2 DF SigTest Resultsa,b,c
Dependent variable: roe9496a.
Predictors: (Constant), quacer96, prodev96, cussur96, empsha96,invrel96, mgmsha96, envcer96, envtra96, envdep96, impuse96,emptra96, empboa96, empcer96, empsur96, equopp96
b.
Standardized residuals are usedc.
Appendix 3 – list of companies A.P. Møller - Mærsk A/S Ambu Auriga Industries Bang & Olufsen Bavarian Nordic BHJ Bioscan Bodilsen Holding Brd. Klee Brdr.A & O Johansen Brdr.Hartmann Bryggerigruppen Carlsberg Chr.Hansen Holding Coloplast Color Print Consenta Holding D/S Norden D/S Orion D/S Torm Danionics Danisco Dantax Dantherm Holding DanTruck-Heden Denka Holding DFDS DLH DSV Egetæpper EuroCom Industries Expedit F.E.Bording F.Junckers Industrier FLS Industries Flügger Funki G. Falbe-Hansen Gabriel Holding Genmab Glunz & Jensen GN Store Nord GPV Industri Group 4 Falck H. Lundbeck
H+H International Harboes Bryggeri Hedegaard Incentive ISS ITH Industri Invest Julius Koch Kompan Københavns Lufthavne Migatronic Mols-Linien MT Højgaard National Industri NEG Micon NESA NeuroSearch NKT Holding Novo Nordisk Novozymes Nowaco Group NTR Holding OBTEC Ove Arkil Holding Per Aarsleff Pharmexa Radiometer Randers Rebslåeri Roblon Rockwool International RTX Telecom Sanistål Satair Schouw & Co. SIS international Skako SP Group Thrane & Thrane Topsil Semiconductor Materials Treka Vestas Wind Systems Wewers Teglværker William Demant Holding Østasiatiske Kompagni Aarhus Oliefabrik
Appendix 4 – Pearson’s correlation, financial variables. 2002:
Correlations
1 ,297** ,552**. ,007 ,000
81 81 81,297** 1 ,652**,007 . ,000
81 89 89,552** ,652** 1,000 ,000 .
81 89 89
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
MB0002
ROA0002
ROE0002
MB0002 ROA0002 ROE0002
Correlation is significant at the 0.01 level (2-tailed).**.
1999:
Correlations
1 ,322** ,294**. ,005 ,010
76 76 76,322** 1 ,752**,005 . ,000
76 83 83,294** ,752** 1,010 ,000 .
76 83 83
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
MB9799
ROA9799
ROE9799
MB9799 ROA9799 ROE9799
Correlation is significant at the 0.01 level (2-tailed).**.
1996: Correlations
1 ,202 ,144. ,093 ,234
70 70 70,202 1 ,644**,093 . ,000
70 75 75,144 ,644** 1,234 ,000 .
70 75 75
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
MB9496
ROA9496
ROE9496
MB9496 ROA9496 ROE9496
Correlation is significant at the 0.01 level (2-tailed).**.
Appendix 5 – scatter plots for performance measures – 2002 2002:
ROA0002
,6,4,20,0-,2-,4-,6-,8
MB0002
300
200
100
0
-100
ROE0002
2,01,51,0,50,0-,5-1,0-1,5
MB0002
300
200
100
0
-100
ROE0002
210-1-2
ROA0002
,6
,4
,2
0,0
-,2
-,4
-,6
-,8
1999:
ROA9799
,3,2,10,0-,1-,2-,3-,4
MB9799
300
200
100
0
-100
ROE9799
,6,4,20,0-,2-,4-,6-,8
MB9799
300
200
100
0
-100
ROE9799
,6,4,20,0-,2-,4-,6-,8
ROA9799
,3
,2
,1
0,0
-,1
-,2
-,3
-,4
1996:
ROA9496
,2,10,0-,1-,2
MB9496
200
100
0
-100
ROE9496
,6,4,2,0-,2-,4-,6-,8-1,0-1,2
MB9496
200
100
0
-100
ROE9496
,6,4,2,0-,2-,4-,6-,8-1,0-1,2
ROA9496
,2
,1
0,0
-,1
-,2
Appendix 6 – developments for all 15 variables1 – 1996 to 2002
quacer
10
11
12
13
14
15
16
17
18
1996 1999 2002
prodev
0
10
20
30
40
50
60
70
1996 1999 2002
1 Adjusted for total number of companies.
cussur
0
1
2
3
4
5
6
7
8
1996 1999 2002
empsha
0
5
10
15
20
25
30
1996 1999 2002
invrel
0
2
4
6
8
10
12
1996 1999 2002
mgmsha
0
5
10
15
20
25
30
35
40
45
50
1996 1999 2002
envcer
0
5
10
15
20
25
30
35
1996 1999 2002
envtra
0
2
4
6
8
10
12
1996 1999 2002
envdep
0
1
2
3
4
5
6
1996 1999 2002
impuse
0
5
10
15
20
25
30
35
1996 1999 2002
emptra
0
5
10
15
20
25
30
35
1996 1999 2002
empboa
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1996 1999 2002
empcer
0
1
2
3
4
5
6
1996 1999 2002
empsur
0
1
2
3
4
5
6
7
8
9
1996 1999 2002
equopp
0
1
2
3
4
5
6
7
8
1996 1999 2002
Appendix 7 – Pearson’s correlation, all independent variables - 2002:
1999:
1996:
Appendix 8 – Pearson’s correlation, category variables 2002:
Correlations
1 ,286** ,293** ,395**. ,007 ,005 ,000
89 89 89 89,286** 1 ,136 ,307**,007 . ,205 ,003
89 89 89 89,293** ,136 1 ,362**,005 ,205 . ,000
89 89 89 89,395** ,307** ,362** 1,000 ,003 ,000 .
89 89 89 89
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
CUS02
INV02
ENV02
EMP02
CUS02 INV02 ENV02 EMP02
Correlation is significant at the 0.01 level (2-tailed).**.
1999:
Correlations
1 ,062 ,117 ,117. ,576 ,289 ,289
84 84 84 84,062 1 ,218* ,218*,576 . ,046 ,046
84 84 84 84,117 ,218* 1 1,000**,289 ,046 . .
84 84 84 84,117 ,218* 1,000** 1,289 ,046 . .
84 84 84 84
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
CUS99
INV99
ENV99
EMP99
CUS99 INV99 ENV99 EMP99
Correlation is significant at the 0.05 level (2-tailed).*.
Correlation is significant at the 0.01 level (2-tailed).**.
1996:
Correlations
1 ,175 ,014 ,315**. ,118 ,904 ,004
81 81 81 81,175 1 ,130 ,158,118 . ,246 ,158
81 81 81 81,014 ,130 1 -,005,904 ,246 . ,965
81 81 81 81,315** ,158 -,005 1,004 ,158 ,965 .
81 81 81 81
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
CUS96
INV96
ENV96
EMP96
CUS96 INV96 ENV96 EMP96
Correlation is significant at the 0.01 level (2-tailed).**.
Appendix 9 – example of simple regression This example of a simple regression against the individual variables only use envcer in 2002 for all four datasets. Data1:
Variables Entered/Removedb
ENVCER02
a . Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,189a ,036 ,025 ,3644996Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), ENVCER02a.
Dependent Variable: ROE0002b.
ANOVAb
,430 1 ,430 3,239 ,075a
11,559 87 ,13311,989 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), ENVCER02a.
Dependent Variable: ROE0002b.
Coefficientsa
-,015 ,047 -,320 ,749,147 ,082 ,189 1,800 ,075
(Constant)ENVCER02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
-4,973 -1,82775,220 1,8875
Case Number1987
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,015208 ,131892 ,034376 ,0699299 89-1,812508 1,902686 ,000000 ,3624226 89
-,709 1,394 ,000 1,000 89-4,973 5,220 ,000 ,994 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
5,004,00
3,002,00
1,000,00
-1,00-2,00
-3,00-4,00
-5,00
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
50
40
30
20
10
0
Std. Dev = ,99 Mean = 0,00
N = 89,00
Data2:
Variables Entered/Removedb
ENVCER02
a . Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,267a ,071 ,061 ,17570Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), ENVCER02a.
Dependent Variable: ROE0002b.
ANOVAb
,204 1 ,204 6,618 ,012a
2,655 86 ,0312,859 87
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), ENVCER02a.
Dependent Variable: ROE0002b.
Coefficientsa
,017 ,023 ,729 ,468,102 ,040 ,267 2,573 ,012
(Constant)ENVCER02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
3,222 ,58-3,531 -,60
Case Number542
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
,0168 ,1187 ,0511 ,04846 89-,6203 ,5662 -,0004 ,17468 88-,709 1,394 ,000 1,000 89
-3,531 3,222 -,002 ,994 88
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
3,002,50
2,001,50
1,00,500,00
-,50-1,00
-1,50-2,00
-2,50-3,00
-3,50
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
30
20
10
0
Std. Dev = ,99 Mean = -,00
N = 88,00
Data3:
Variables Entered/Removedb
ENVCER02
a . Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,335a ,112 ,102 ,1293973Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), ENVCER02a.
Dependent Variable: ROE0002b.
ANOVAb
,178 1 ,178 10,609 ,002a
1,406 84 ,0171,584 85
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), ENVCER02a.
Dependent Variable: ROE0002b.
Coefficientsa
,031 ,017 1,833 ,070,096 ,030 ,335 3,257 ,002
(Constant)ENVCER02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: ROE0002a.
Residuals Statisticsa
,031422 ,127581 ,063835 ,0457133 89-,286981 ,309306 -,001131 ,1286344 86
-,709 1,394 ,000 1,000 89-2,218 2,390 -,009 ,994 86
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
2,502,25
2,001,75
1,501,25
1,00,75,50,250,00
-,25-,50
-,75-1,00
-1,25-1,50
-1,75-2,00
-2,25
Histogram
Dependent Variable: ROE0002Fr
eque
ncy
16
14
12
10
8
6
4
2
0
Std. Dev = ,99 Mean = -,01
N = 86,00
Ranked:
Variables Entered/Removedb
ENVCER02
a . Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: RANK of ROE0002b.
Model Summaryb
,310a ,096 ,086 24,704Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), ENVCER02a.
Dependent Variable: RANK of ROE0002b.
ANOVAb
5642,952 1 5642,952 9,246 ,003a
53097,048 87 610,31158740,000 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), ENVCER02a.
Dependent Variable: RANK of ROE0002b.
Coefficientsa
39,322 3,216 12,226 ,00016,845 5,540 ,310 3,041 ,003
(Constant)ENVCER02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: RANK of ROE0002a.
Residuals Statisticsa
39,32 56,17 45,00 8,008 89-48,17 49,68 ,00 24,564 89-,709 1,394 ,000 1,000 89
-1,950 2,011 ,000 ,994 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: RANK of ROE0002a.
Regression Standardized Residual
2,001,75
1,501,25
1,00,75,50,250,00
-,25-,50
-,75-1,00
-1,25-1,50
-1,75-2,00
Histogram
Dependent Variable: RANK of ROE0002Fr
eque
ncy
10
8
6
4
2
0
Std. Dev = ,99 Mean = 0,00
N = 89,00
Appendix 10 – example of simple category regression This example of a simple regression against the category variables only use env for 2002 and all four datasets. Data1:
Variables Entered/Removedb
ENV02a . EnterModel1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,189a ,036 ,024 ,3645598Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), ENV02a.
Dependent Variable: ROE0002b.
ANOVAb
,427 1 ,427 3,209 ,077a
11,563 87 ,13311,989 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), ENV02a.
Dependent Variable: ROE0002b.
Coefficientsa
-,023 ,050 -,453 ,651,275 ,153 ,189 1,791 ,077
(Constant)ENV02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
-4,951 -1,82775,240 1,8875
Case Number1987
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,022713 ,183271 ,034376 ,0696189 89-1,805003 1,910191 ,000000 ,3624825 89
-,820 2,139 ,000 1,000 89-4,951 5,240 ,000 ,994 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
5,004,00
3,002,00
1,000,00
-1,00-2,00
-3,00-4,00
-5,00
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
50
40
30
20
10
0
Std. Dev = ,99 Mean = 0,00
N = 89,00
Data2:
Variables Entered/Removedb
ENV02a . EnterModel1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,304a ,092 ,082 ,17372Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), ENV02a.
Dependent Variable: ROE0002b.
ANOVAb
,264 1 ,264 8,737 ,004a
2,595 86 ,0302,859 87
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), ENV02a.
Dependent Variable: ROE0002b.
Coefficientsa
,006 ,024 ,249 ,804,217 ,073 ,304 2,956 ,004
(Constant)ENV02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
3,321 ,58-3,509 -,60
Case Number542
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
,0060 ,1689 ,0511 ,05505 89-,6095 ,5769 -,0005 ,17272 88
-,820 2,139 ,000 1,000 89-3,509 3,321 -,003 ,994 88
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
3,503,00
2,502,00
1,501,00
,500,00-,50
-1,00-1,50
-2,00-2,50
-3,00-3,50
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
30
20
10
0
Std. Dev = ,99 Mean = -,00
N = 88,00
Data 3: Variables Entered/Removedb
ENV02a . EnterModel1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,354a ,125 ,115 ,1284534Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), ENV02a.
Dependent Variable: ROE0002b.
ANOVAb
,198 1 ,198 12,004 ,001a
1,386 84 ,0171,584 85
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), ENV02a.
Dependent Variable: ROE0002b.
Coefficientsa
,024 ,018 1,351 ,180,190 ,055 ,354 3,465 ,001
(Constant)ENV02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: ROE0002a.
Residuals Statisticsa
,024251 ,167076 ,063835 ,0482724 89-,313639 ,316477 -,001381 ,1276958 86
-,820 2,139 ,000 1,000 89-2,442 2,464 -,011 ,994 86
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
2,502,00
1,501,00
,500,00-,50
-1,00-1,50
-2,00-2,50
Histogram
Dependent Variable: ROE0002Fr
eque
ncy
16
14
12
10
8
6
4
2
0
Std. Dev = ,99 Mean = -,01
N = 86,00
Ranked:
Variables Entered/Removedb
ENV02a . EnterModel1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: RANK of ROE0002b.
Model Summaryb
,334a ,112 ,102 24,488Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), ENV02a.
Dependent Variable: RANK of ROE0002b.
ANOVAb
6570,448 1 6570,448 10,957 ,001a
52169,552 87 599,65058740,000 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), ENV02a.
Dependent Variable: RANK of ROE0002b.
Coefficientsa
37,914 3,364 11,269 ,00034,088 10,298 ,334 3,310 ,001
(Constant)ENV02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: RANK of ROE0002a.
Residuals Statisticsa
37,91 63,48 45,00 8,641 89-44,44 51,09 ,00 24,348 89
-,820 2,139 ,000 1,000 89-1,815 2,086 ,000 ,994 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: RANK of ROE0002a.
Regression Standardized Residual
2,001,75
1,501,25
1,00,75,50,250,00
-,25-,50
-,75-1,00
-1,25-1,50
-1,75
Histogram
Dependent Variable: RANK of ROE0002Fr
eque
ncy
10
8
6
4
2
0
Std. Dev = ,99 Mean = 0,00
N = 89,00
Appendix 11 – example of multiple regressions for all variables This example of the multiple regression including all 15 variables is only for 2002. Data1:
Variables Entered/Removedb
EQUOPP02,INVREL02,ENVDEP02,EMPTRA02,EMPBOA02,MGMSHA02,PRODEV02,EMPCER02,ENVTRA02,QUACER02,EMPSHA02,CUSSUR02,EMPSUR02,ENVCER02,IMPUSE02
a
. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,343a ,118 -,064 ,3806688Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EQUOPP02, INVREL02,ENVDEP02, EMPTRA02, EMPBOA02, MGMSHA02,PRODEV02, EMPCER02, ENVTRA02, QUACER02,EMPSHA02, CUSSUR02, EMPSUR02, ENVCER02,IMPUSE02
a.
Dependent Variable: ROE0002b.
ANOVAb
1,411 15 ,094 ,649 ,824a
10,578 73 ,14511,989 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EQUOPP02, INVREL02, ENVDEP02, EMPTRA02,EMPBOA02, MGMSHA02, PRODEV02, EMPCER02, ENVTRA02, QUACER02,EMPSHA02, CUSSUR02, EMPSUR02, ENVCER02, IMPUSE02
a.
Dependent Variable: ROE0002b.
Coefficientsa
-,117 ,090 -1,293 ,200-,014 ,122 -,014 -,111 ,912 ,713 1,403,069 ,097 ,087 ,714 ,477 ,815 1,226,116 ,183 ,085 ,634 ,528 ,672 1,488,174 ,110 ,215 1,576 ,119 ,647 1,546
-,023 ,134 -,020 -,169 ,867 ,834 1,200,078 ,092 ,107 ,855 ,396 ,775 1,290,109 ,112 ,140 ,971 ,335 ,580 1,723,159 ,172 ,137 ,926 ,358 ,554 1,806,097 ,190 ,061 ,510 ,611 ,853 1,173
-,019 ,114 -,025 -,170 ,866 ,566 1,766-,084 ,112 -,110 -,750 ,456 ,566 1,767-,063 ,102 -,074 -,617 ,539 ,843 1,186,015 ,205 ,009 ,071 ,943 ,731 1,368,123 ,181 ,096 ,680 ,498 ,605 1,652
-,143 ,180 -,105 -,797 ,428 ,694 1,441
(Constant)QUACER02PRODEV02CUSSUR02EMPSHA02INVREL02MGMSHA02ENVCER02ENVTRA02ENVDEP02IMPUSE02EMPTRA02EMPBOA02EMPCER02EMPSUR02EQUOPP02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
-4,495 -1,82774,626 1,8875
Case Number1987
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,253615 ,327424 ,034376 ,1266174 89-1,710969 1,760885 ,000000 ,3467108 89
-2,274 2,314 ,000 1,000 89-4,495 4,626 ,000 ,911 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
4,504,00
3,503,00
2,502,00
1,501,00
,500,00-,50
-1,00-1,50
-2,00-2,50
-3,00-3,50
-4,00-4,50
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
50
40
30
20
10
0
Std. Dev = ,91 Mean = 0,00
N = 89,00
Data2:
Variables Entered/Removedb
EQUOPP02,INVREL02,ENVDEP02,EMPTRA02,EMPBOA02,MGMSHA02,PRODEV02,EMPCER02,ENVTRA02,QUACER02,EMPSHA02,CUSSUR02,EMPSUR02,ENVCER02,IMPUSE02
a
. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,439a ,193 ,024 ,17906Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EQUOPP02, INVREL02,ENVDEP02, EMPTRA02, EMPBOA02, MGMSHA02,PRODEV02, EMPCER02, ENVTRA02, QUACER02,EMPSHA02, CUSSUR02, EMPSUR02, ENVCER02,IMPUSE02
a.
Dependent Variable: ROE0002b.
ANOVAb
,551 15 ,037 1,145 ,335a
2,308 72 ,0322,859 87
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EQUOPP02, INVREL02, ENVDEP02, EMPTRA02,EMPBOA02, MGMSHA02, PRODEV02, EMPCER02, ENVTRA02, QUACER02,EMPSHA02, CUSSUR02, EMPSUR02, ENVCER02, IMPUSE02
a.
Dependent Variable: ROE0002b.
Coefficientsa
,013 ,043 ,299 ,766,049 ,058 ,106 ,847 ,400 ,713 1,403
-,017 ,046 -,044 -,372 ,711 ,815 1,226,017 ,086 ,026 ,198 ,843 ,672 1,488
-,086 ,052 -,218 -1,654 ,102 ,647 1,546,036 ,064 ,065 ,559 ,578 ,834 1,200,037 ,043 ,104 ,863 ,391 ,775 1,290,041 ,053 ,107 ,768 ,445 ,580 1,723
-,028 ,081 -,048 -,339 ,736 ,554 1,806,014 ,090 ,018 ,160 ,873 ,853 1,173,093 ,054 ,241 1,712 ,091 ,566 1,766,045 ,053 ,120 ,851 ,398 ,566 1,767
-,062 ,048 -,149 -1,295 ,199 ,843 1,186,059 ,097 ,075 ,607 ,546 ,731 1,368,002 ,086 ,003 ,023 ,982 ,605 1,652
-,055 ,085 -,082 -,648 ,519 ,694 1,441
(Constant)QUACER02PRODEV02CUSSUR02EMPSHA02INVREL02MGMSHA02ENVCER02ENVTRA02ENVDEP02IMPUSE02EMPTRA02EMPBOA02EMPCER02EMPSUR02EQUOPP02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
3,280 ,58-3,074 -,60
Case Number542
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,1219 ,2499 ,0511 ,07955 89-,5503 ,5873 -,0016 ,16232 88-2,176 2,498 ,000 1,000 89-3,074 3,280 -,009 ,907 88
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
3,002,50
2,001,50
1,00,500,00
-,50-1,00
-1,50-2,00
-2,50-3,00
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
16
14
12
10
8
6
4
2
0
Std. Dev = ,91 Mean = -,01
N = 88,00
Data 3:
Variables Entered/Removedb
EQUOPP02,INVREL02,ENVDEP02,EMPTRA02,EMPBOA02,MGMSHA02,PRODEV02,EMPCER02,ENVTRA02,QUACER02,EMPSHA02,CUSSUR02,EMPSUR02,ENVCER02,IMPUSE02
a
. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,466a ,217 ,049 ,1331001Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EQUOPP02, INVREL02,ENVDEP02, EMPTRA02, EMPBOA02, MGMSHA02,PRODEV02, EMPCER02, ENVTRA02, QUACER02,EMPSHA02, CUSSUR02, EMPSUR02, ENVCER02,IMPUSE02
a.
Dependent Variable: ROE0002b.
ANOVAb
,344 15 ,023 1,295 ,229a
1,240 70 ,0181,584 85
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EQUOPP02, INVREL02, ENVDEP02, EMPTRA02,EMPBOA02, MGMSHA02, PRODEV02, EMPCER02, ENVTRA02, QUACER02,EMPSHA02, CUSSUR02, EMPSUR02, ENVCER02, IMPUSE02
a.
Dependent Variable: ROE0002b.
Coefficientsa
,025 ,032 ,765 ,447,011 ,043 ,031 ,245 ,807 ,713 1,403
-,027 ,035 -,093 -,794 ,430 ,815 1,226,014 ,065 ,029 ,223 ,824 ,672 1,488
-,005 ,039 -,018 -,137 ,891 ,647 1,546,013 ,048 ,031 ,267 ,790 ,834 1,200,046 ,033 ,169 1,404 ,165 ,775 1,290,060 ,040 ,209 1,509 ,136 ,580 1,723,001 ,061 ,003 ,022 ,982 ,554 1,806,025 ,068 ,042 ,367 ,715 ,853 1,173,059 ,041 ,203 1,447 ,152 ,566 1,766,016 ,040 ,056 ,397 ,692 ,566 1,767
-,053 ,036 -,167 -1,451 ,151 ,843 1,186,004 ,073 ,007 ,057 ,955 ,731 1,368,017 ,065 ,037 ,271 ,787 ,605 1,652
-,043 ,064 -,086 -,679 ,499 ,694 1,441
(Constant)QUACER02PRODEV02CUSSUR02EMPSHA02INVREL02MGMSHA02ENVCER02ENVTRA02ENVDEP02IMPUSE02EMPTRA02EMPBOA02EMPCER02EMPSUR02EQUOPP02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,098946 ,201609 ,063835 ,0636163 89-,297798 ,316155 -,001920 ,1205824 86
-2,559 2,166 ,000 1,000 89-2,237 2,375 -,014 ,906 86
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
2,502,25
2,001,75
1,501,25
1,00,75,50,250,00
-,25-,50
-,75-1,00
-1,25-1,50
-1,75-2,00
-2,25
Histogram
Dependent Variable: ROE0002Fr
eque
ncy
16
14
12
10
8
6
4
2
0
Std. Dev = ,91 Mean = -,01
N = 86,00
Ranked:
Variables Entered/Removedb
EQUOPP02,INVREL02,ENVDEP02,EMPTRA02,EMPBOA02,MGMSHA02,PRODEV02,EMPCER02,ENVTRA02,QUACER02,EMPSHA02,CUSSUR02,EMPSUR02,ENVCER02,IMPUSE02
a
. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: RANK of ROE0002b.
Model Summaryb
,502a ,252 ,099 24,528Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EQUOPP02, INVREL02,ENVDEP02, EMPTRA02, EMPBOA02, MGMSHA02,PRODEV02, EMPCER02, ENVTRA02, QUACER02,EMPSHA02, CUSSUR02, EMPSUR02, ENVCER02,IMPUSE02
a.
Dependent Variable: RANK of ROE0002b.
ANOVAb
14821,732 15 988,115 1,642 ,083a
43918,268 73 601,62058740,000 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EQUOPP02, INVREL02, ENVDEP02, EMPTRA02,EMPBOA02, MGMSHA02, PRODEV02, EMPCER02, ENVTRA02, QUACER02,EMPSHA02, CUSSUR02, EMPSUR02, ENVCER02, IMPUSE02
a.
Dependent Variable: RANK of ROE0002b.
Coefficientsa
31,511 5,816 5,418 ,000-1,425 7,833 -,022 -,182 ,856 ,713 1,4031,642 6,263 ,029 ,262 ,794 ,815 1,2266,640 11,781 ,070 ,564 ,575 ,672 1,4888,535 7,108 ,151 1,201 ,234 ,647 1,546
-2,027 8,653 -,026 -,234 ,815 ,834 1,20012,570 5,906 ,245 2,128 ,037 ,775 1,29010,442 7,220 ,192 1,446 ,152 ,580 1,723
3,948 11,062 ,049 ,357 ,722 ,554 1,80610,118 12,228 ,091 ,828 ,411 ,853 1,173
9,504 7,372 ,173 1,289 ,201 ,566 1,766-2,474 7,202 -,046 -,343 ,732 ,566 1,767
-10,660 6,565 -,179 -1,624 ,109 ,843 1,186-1,882 13,205 -,017 -,142 ,887 ,731 1,3683,758 11,684 ,042 ,322 ,749 ,605 1,652
-10,676 11,595 -,112 -,921 ,360 ,694 1,441
(Constant)QUACER02PRODEV02CUSSUR02EMPSHA02INVREL02MGMSHA02ENVCER02ENVTRA02ENVDEP02IMPUSE02EMPTRA02EMPBOA02EMPCER02EMPSUR02EQUOPP02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: RANK of ROE0002a.
Residuals Statisticsa
11,82 75,06 45,00 12,978 89-55,06 52,49 ,00 22,340 89-2,557 2,317 ,000 1,000 89-2,245 2,140 ,000 ,911 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: RANK of ROE0002a.
Regression Standardized Residual
2,252,00
1,751,50
1,251,00
,75,50,250,00-,25
-,50-,75
-1,00-1,25
-1,50-1,75
-2,00-2,25
Histogram
Dependent Variable: RANK of ROE0002Fr
eque
ncy
10
8
6
4
2
0
Std. Dev = ,91 Mean = 0,00
N = 89,00
Appendix 12 – example of multiple regressions for categories. This example of the multiple regressions for the category variables is only included for 2002. Data1:
Variables Entered/Removedb
EMP02,INV02,ENV02,CUS02
a. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,295a ,087 ,043 ,3610255Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EMP02, INV02, ENV02, CUS02a.
Dependent Variable: ROE0002b.
ANOVAb
1,041 4 ,260 1,996 ,103a
10,949 84 ,13011,989 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EMP02, INV02, ENV02, CUS02a.
Dependent Variable: ROE0002b.
Coefficientsa
-,110 ,070 -1,565 ,121,133 ,174 ,090 ,763 ,448 ,789 1,267,256 ,138 ,207 1,853 ,067 ,874 1,144,239 ,165 ,164 1,443 ,153 ,842 1,187
-,160 ,237 -,082 -,675 ,502 ,742 1,347
(Constant)CUS02INV02ENV02EMP02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
-4,758 -1,82775,174 1,8875
Case Number1987
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,142011 ,361939 ,034376 ,1087451 89-1,717625 1,867967 ,000000 ,3527249 89
-1,622 3,012 ,000 1,000 89-4,758 5,174 ,000 ,977 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
5,004,00
3,002,00
1,000,00
-1,00-2,00
-3,00-4,00
-5,00
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
40
30
20
10
0
Std. Dev = ,98 Mean = 0,00
N = 89,00
Data2:
Variables Entered/Removedb
EMP02,INV02,ENV02,CUS02
a. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,315a ,099 ,056 ,17617Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EMP02, INV02, ENV02, CUS02a.
Dependent Variable: ROE0002b.
ANOVAb
,283 4 ,071 2,279 ,068a
2,576 83 ,0312,859 87
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EMP02, INV02, ENV02, CUS02a.
Dependent Variable: ROE0002b.
Coefficientsa
-,002 ,035 -,072 ,943,061 ,086 ,083 ,711 ,479 ,789 1,267
-,003 ,068 -,005 -,045 ,964 ,874 1,144,216 ,081 ,303 2,667 ,009 ,842 1,187
-,060 ,116 -,063 -,520 ,604 ,742 1,347
(Constant)CUS02INV02ENV02EMP02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
3,208 ,58-3,515 -,60
Case Number542
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,0166 ,1884 ,0511 ,05703 89-,6193 ,5651 -,0004 ,17210 88-1,188 2,406 ,000 1,000 89-3,515 3,208 -,002 ,977 88
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
3,002,50
2,001,50
1,00,500,00
-,50-1,00
-1,50-2,00
-2,50-3,00
-3,50
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
30
20
10
0
Std. Dev = ,98 Mean = -,00
N = 88,00
Data 3:
Variables Entered/Removedb
EMP02,INV02,ENV02,CUS02
a. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,388a ,151 ,109 ,1288724Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EMP02, INV02, ENV02, CUS02a.
Dependent Variable: ROE0002b.
ANOVAb
,239 4 ,060 3,595 ,009a
1,345 81 ,0171,584 85
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EMP02, INV02, ENV02, CUS02a.
Dependent Variable: ROE0002b.
Coefficientsa
,013 ,026 ,514 ,609-,008 ,063 -,014 -,125 ,901 ,789 1,267,075 ,050 ,164 1,495 ,139 ,874 1,144,199 ,060 ,369 3,307 ,001 ,842 1,187
-,067 ,086 -,092 -,776 ,440 ,742 1,347
(Constant)CUS02INV02ENV02EMP02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,016159 ,209512 ,063835 ,0530079 89-,301952 ,327593 -,000989 ,1259148 86
-1,509 2,748 ,000 1,000 89-2,343 2,542 -,008 ,977 86
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
2,502,25
2,001,75
1,501,25
1,00,75,50,250,00
-,25-,50
-,75-1,00
-1,25-1,50
-1,75-2,00
-2,25
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
14
12
10
8
6
4
2
0
Std. Dev = ,98 Mean = -,01
N = 86,00
Ranked:
Variables Entered/Removedb
EMP02,INV02,ENV02,CUS02
a. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: RANK of ROE0002b.
Model Summaryb
,446a ,199 ,161 23,668Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EMP02, INV02, ENV02, CUS02a.
Dependent Variable: RANK of ROE0002b.
ANOVAb
11687,237 4 2921,809 5,216 ,001a
47052,763 84 560,15258740,000 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EMP02, INV02, ENV02, CUS02a.
Dependent Variable: RANK of ROE0002b.
Coefficientsa
31,975 4,612 6,933 ,0004,656 11,428 ,045 ,407 ,685 ,789 1,267
25,607 9,050 ,296 2,830 ,006 ,874 1,14434,280 10,844 ,336 3,161 ,002 ,842 1,187
-20,832 15,507 -,152 -1,343 ,183 ,742 1,347
(Constant)CUS02INV02ENV02EMP02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: RANK of ROE0002a.
Residuals Statisticsa
25,19 76,31 45,00 11,524 89-49,62 52,03 ,00 23,123 89-1,719 2,717 ,000 1,000 89-2,096 2,198 ,000 ,977 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: RANK of ROE0002a.
Regression Standardized Residual
2,252,00
1,751,50
1,251,00
,75,50,250,00-,25
-,50-,75
-1,00-1,25
-1,50-1,75
-2,00
Histogram
Dependent Variable: RANK of ROE0002
Freq
uenc
y
14
12
10
8
6
4
2
0
Std. Dev = ,98 Mean = 0,00
N = 89,00
Appendix 13 – final model for multiple regressions for 2002 This example of the finale model only includes the absolute final, that is: model 3. Model 3: Mb:
Variables Entered/Removedb
EMPBOA02,ENVCER02,EMPSHA02,MGMSHA02
a
. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: MB0002b.
Model Summaryb
,337a ,114 ,067 42,08913Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EMPBOA02, ENVCER02,EMPSHA02, MGMSHA02
a.
Dependent Variable: MB0002b.
ANOVAb
17249,065 4 4312,266 2,434 ,054a
134633,6 76 1771,495151882,7 80
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EMPBOA02, ENVCER02, EMPSHA02, MGMSHA02a.
Dependent Variable: MB0002b.
Coefficientsa
9,322 7,635 1,221 ,22629,684 10,939 ,312 2,714 ,008 ,885 1,130-1,084 10,210 -,013 -,106 ,916 ,840 1,19011,033 10,178 ,120 1,084 ,282 ,946 1,057-2,673 10,867 -,027 -,246 ,806 ,996 1,004
(Constant)EMPSHA02MGMSHA02ENVCER02EMPBOA02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: MB0002a.
Casewise Diagnosticsa
4,753 246,334,847 243,00
Case Number8587
Std. Residual MB0002
Dependent Variable: MB0002a.
Residuals Statisticsa
5,5655 50,0393 20,5043 14,68378 89-43,5293 203,9933 -,5984 40,93976 81
-1,017 2,011 ,000 1,000 89-1,034 4,847 -,014 ,973 81
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: MB0002a.
Regression Standardized Residual
4,504,00
3,503,00
2,502,00
1,501,00
,500,00-,50
-1,00
Histogram
Dependent Variable: MB0002
Freq
uenc
y
30
20
10
0
Std. Dev = ,97 Mean = -,01
N = 81,00
roa: Variables Entered/Removedb
EMPBOA02,ENVCER02,EMPSHA02,MGMSHA02
a
. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROA0002b.
Model Summaryb
,330a ,109 ,067 ,1224226Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EMPBOA02, ENVCER02,EMPSHA02, MGMSHA02
a.
Dependent Variable: ROA0002b.
ANOVAb
,154 4 ,039 2,573 ,044a
1,259 84 ,0151,413 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EMPBOA02, ENVCER02, EMPSHA02, MGMSHA02a.
Dependent Variable: ROA0002b.
Coefficientsa
,009 ,021 ,430 ,668,022 ,030 ,079 ,717 ,475 ,885 1,130,019 ,028 ,075 ,665 ,508 ,840 1,190,066 ,028 ,247 2,336 ,022 ,946 1,057
-,043 ,030 -,146 -1,417 ,160 ,996 1,004
(Constant)EMPSHA02MGMSHA02ENVCER02EMPBOA02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: ROA0002a.
Casewise Diagnosticsa
-5,776 -,69803,105 ,4109
Case Number587
Std. Residual ROA0002
Dependent Variable: ROA0002a.
Residuals Statisticsa
-,033607 ,115620 ,036645 ,0418695 89-,707096 ,380068 ,000000 ,1196080 89
-1,678 1,886 ,000 1,000 89-5,776 3,105 ,000 ,977 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROA0002a.
Regression Standardized Residual
3,002,50
2,001,50
1,00,500,00
-,50-1,00
-1,50-2,00
-2,50-3,00
-3,50-4,00
-4,50-5,00
-5,50-6,00
Histogram
Dependent Variable: ROA0002
Freq
uenc
y
40
30
20
10
0
Std. Dev = ,98 Mean = 0,00
N = 89,00
roe: Variables Entered/Removedb
EMPBOA02,ENVCER02,EMPSHA02,MGMSHA02
a
. Enter
Model1
VariablesEntered
VariablesRemoved Method
All requested variables entered.a.
Dependent Variable: ROE0002b.
Model Summaryb
,293a ,086 ,042 ,3612459Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), EMPBOA02, ENVCER02,EMPSHA02, MGMSHA02
a.
Dependent Variable: ROE0002b.
ANOVAb
1,027 4 ,257 1,968 ,107a
10,962 84 ,13011,989 88
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), EMPBOA02, ENVCER02, EMPSHA02, MGMSHA02a.
Dependent Variable: ROE0002b.
Coefficientsa
-,065 ,062 -1,043 ,300,128 ,090 ,159 1,433 ,156 ,885 1,130,075 ,084 ,102 ,897 ,372 ,840 1,190,120 ,083 ,154 1,435 ,155 ,946 1,057
-,065 ,089 -,077 -,734 ,465 ,996 1,004
(Constant)EMPSHA02MGMSHA02ENVCER02EMPBOA02
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig. Tolerance VIFCollinearity Statistics
Dependent Variable: ROE0002a.
Casewise Diagnosticsa
-4,879 -1,82775,050 1,8875
Case Number1987
Std. Residual ROE0002
Dependent Variable: ROE0002a.
Residuals Statisticsa
-,130422 ,257627 ,034376 ,1080441 89-1,762552 1,824351 ,000000 ,3529402 89
-1,525 2,066 ,000 1,000 89-4,879 5,050 ,000 ,977 89
Predicted ValueResidualStd. Predicted ValueStd. Residual
Minimum Maximum Mean Std. Deviation N
Dependent Variable: ROE0002a.
Regression Standardized Residual
5,004,00
3,002,00
1,000,00
-1,00-2,00
-3,00-4,00
-5,00
Histogram
Dependent Variable: ROE0002
Freq
uenc
y
40
30
20
10
0
Std. Dev = ,98 Mean = 0,00
N = 89,00
Appendix 14 – example independent sample t-tests This example of the independent sample t-tests is only included for envcer for 2002 and all three performance measures and data1 and ranked. Data1:
Ranked: